Polysaccharide degradation in an Antarctic bacterium: Discovery of glycoside hydrolases from remote regions of the sequence space

Glycoside hydrolases (GHs) are enzymes involved in the degradation of oligosaccharides and polysaccharides. The sequence space of GHs is rapidly expanding due to the increasing number of available sequences. This expansion paves the way for the discovery of novel enzymes with peculiar structural and functional properties. This work is focused on two GHs, Ps_GH5 and Ps_GH50, from the genome of the Antarctic bacterium Pseudomonas sp. ef1. These enzymes are in an unexplored region of the sequence space of their respective GH families, not allowing a reliable sequence-based function prediction. For this reason, a computational pipeline was developed that combines deep learning "dynamic docking" on AlphaFold 3D models with physics-based molecular dynamics simulations to infer their substrate specificity. From in silico screening of a repertoire of potential oligosaccharides, only xylooligosaccharides for Ps_GH5 and galactooligosaccharides for Ps_GH50 emerged as catalytically competent substrates. Biochemical characterization agrees with computational simulations indicating that Ps_GH5 is an endo-β-xylanase, and Ps_GH50 is active mainly on small galactooligosaccharides. In conclusion, this study identifies two novel GHs subfamilies placed in remote regions of the sequence space and highlights the efficacy of substrate specificity prediction by computational approaches in the discovery of new enzymes.

Prediction of interface between regions of varying degrees of order or disorderness in intrinsically disordered proteins from dihedral angles

Intrinsically disordered proteins (IDPs) are proteins that do not form uniquely defined three-dimensional (3-D) structures. Experimental research on IDPs is difficult since they go against the traditional protein structure-function paradigm. Although there are several predictors of disorder based on amino acid sequences, but very limited based on the 3-D structures of proteins. Dihedral angles have a significant role in predicting protein structure because they establish a protein's backbone, which, coupled with its side chain, establishes its overall shape. Here, we have carried out atomistic Molecular Dynamics (MD) simulations on four different proteins: one ordered protein (Monellin), two partially disordered proteins (p53-TAD and Amyloid beta (Aβ1-42) peptide), and one completely disordered protein (Histatin 5). The MD simulation trajectories for the corresponding four proteins were used to conduct dihedral angle (ϕ and ѱ) analysis. Then, the average dihedral angles for each of the residues were calculated and plotted against the residue index. We noticed steep rises or falls in the average ϕ value at certain locations in the plot. These sudden shifts in the average ϕ value reflect the interface between regions of varying degrees of order or disorderness in intrinsically disordered proteins. Using this method, the probable conformer of a protein with a higher degree of disorder can be found among the ensembles of structures sampled during the MD simulations. The results of our study offer new understandings on precisely identifying regions of various degrees of disorder in intrinsically disordered proteins.

Biochemical and molecular docking-based strategies of Acalypha indica and Boerhavia diffusa extract by targeting bacterial strains and cancer proteins

Antibiotic-resistant microbes have emerged around the world, presenting a risk to health. Plant-derived drugs have become a potential source for the production of antibiotic-resistant drugs and cancer therapies. In this study, we investigated the antibacterial, cytotoxic and antioxidant properties of Acalypha indica and Boerhavia diffusa, and conducted in silico molecular docking experiments against EGFR and VEGFR-2 proteins. The metabolic extract of A. indica inhibited Streptococcus iniae and Staphylococcus sciuri with inhibition zones of 21.66 ± 0.57 mm and 20.33 ± 0.57 mm, respectively. The B. diffusa leaf extract produced inhibition zones of 20.3333 ± 0.5773 mm and 20.33 ± 0.57 mm against Streptococcus iniae and Edwardsiella anguillarum, respectively. A. indica and B. diffusa extracts had toxicities of 162.01 μg/ml and 175.6 μg/ml, respectively. Moreover, B. diffusa (IC50 =154.42 µg/ml) leaf extract exhibited moderately higher antioxidant activity compared with the A. indica (IC50 = 218.97 µg/ml) leaf extract. Multiple interactions were observed at Leu694, Met769 and Leu820 sites for EGFR and at Asp1046 and Cys1045 sites for VEGFR during the molecular docking study. CID-235030, CID-70825 and CID-156619353 had binding energies of -7.6 kJ/mol, -7.5 kJ/mol and -7.6 kJ/mol, respectively, with EGFR protein. VEGFR-2 protein had docking energies of -7.5 kJ/mol, -7.6 kJ/mol and -7.3 kJ/mol, respectively, for CID-6420353, CID-156619353 and CID-70825 compounds. The MD simulation trajectories revealed the hit compound; CID-235030 and EGFR complex, CID-6420353 and VEGFR-2 exhibit stable profile in the root mean square deviation (RMSD), radius of gyration (Rg), solvent accessible surface area (SASA), hydrogen bond and root mean square fluctuation (RMSF) and the binding free energy by MM-PBSA method. This study indicates that methanol extracts of A. indica and B. diffusa may play a crucial role in developing antibiotic-resistant and cancer drugs.

Drug repurposing using artificial intelligence, molecular docking, and hybrid approaches: A comprehensive review in general diseases vs Alzheimer's disease

BACKGROUND

Alzheimer's disease (AD), the most prevalent form of dementia, remains enigmatic in its origins despite the widely accepted "amyloid hypothesis," which implicates amyloid-beta peptide aggregates in its pathogenesis and progression. Despite advancements in technology and healthcare, the incidence of AD continues to rise. The traditional drug development process remains time-consuming, often taking years to bring an AD treatment to market. Drug repurposing has emerged as a promising strategy for developing cost-effective and efficient therapeutic options by identifying new uses for existing approved drugs, thus accelerating drug development.

OBJECTIVES

This study aimed to examine two key drug repurposing methodologies in general diseases and specifically in AD, which are artificial intelligent (AI) approach and molecular docking approach. In addition, the hybrid approach that integrates AI with molecular docking techniques will be explored too.

METHODOLOGY

This study systematically compiled a comprehensive collection of relevant academic articles, scientific papers, and research studies which were published up until November 2024 (as of the writing of this review paper). The final selection of papers was filtered to include studies related to Alzheimer's disease and general diseases, and then categorized into three groups: AI articles, molecular docking articles, and hybrid articles.

RESULTS

As a result, 331 papers were identified that employed AI for drug repurposing in general diseases, and 58 papers focused specifically in AD. For molecular docking in drug repurposing, 588 papers addressed general diseases, while 46 papers were dedicated to AD. The hybrid approach combining AI and molecular docking in drug repurposing has 52 papers for general diseases and 9 for AD. A comparative review was done across the methods, results, strengths, and limitations in those studies. Challenges of drug repurposing in AD are explored and future prospects are proposed.

DISCUSSION AND CONCLUSION

Drug repurposing emerges as a compelling and effective strategy within AD research. Both AI and molecular docking methods exhibit significant potential in this domain. AI algorithms yield more precise predictions, thus facilitating the exploration of new therapeutic avenues for existing drugs. Similarly, molecular docking techniques revolutionize drug-target interaction modelling, employing refined algorithms to screen extensive drug databases against specific target proteins. This review offers valuable insights for guiding the utilization of AI, molecular docking, or their hybrid in AD drug repurposing endeavors. The hope is to speed up the timeline of drug discovery which could improve the therapeutic approach to AD.

Exploring the Anticancer Potential of Furanpydone A: A Computational Study on its Inhibition of MTHFD2 Across Diverse Cancer Cell Lines

Cancer poses a significant global health challenge due to its high mortality rate and complex treatment strategies. Methylenetetrahydrofolate dehydrogenase 2 (MTHFD2), which is notably overexpressed in various malignancies, represents a promising target for anticancer drug development. Furanpydone A, a new 4-hydroxy-2-pyridone alkaloid isolated from the endophytic fungus Arthrinium sp. GZWMJZ-606, has shown potent inhibitory activity against several cancer cell lines. This study provides the first computational evaluation of furanpydone A, focusing on its potential inhibition of MTHFD2 through molecular docking and 200 ns molecular dynamics (MD) simulations. Molecular docking revealed a binding free energy of -8.08 kcal/mol for furanpydone A, comparable to the control compound DS44960156 (-8.13 kcal/mol), indicating stable interactions with the MTHFD2 active site. MD simulations confirmed the structural stability of the furanpydone A-MTHFD2 complex, with RMSD values ranging from 1.5 to 2.9 Å, RMSF values below 4 Å, and a radius of gyration (Rg) of 26.7 Å. Furanpydone A maintained approximately four consistent hydrogen bonds throughout the simulation. Analysis of furanpydone A binding pose orientations and interactions with the MTHFD2 enzyme at 0 ns, 40 ns, 80 ns, 120 ns, 160 ns, and 200 ns revealed consistent and stable binding. MM-PBSA analysis showed a binding free energy (ΔGbind) of -23.57 ± 0.13 kcal/mol, with electrostatic and van der Waals interactions contributing significantly, suggesting competitive binding affinity to the control compound (-25.32 ± 0.11 kcal/mol). The contribution of individual amino acid residues, including key residues such as ARG43, TYR84, ASN87, LYS88, GLN132, and PRO314, indicated strong interactions that support the stability of the furanpydone A-MTHFD2 complex. ADMET predictions indicated that furanpydone A met key drug-likeness criteria and demonstrated good oral bioavailability, suitable distribution profile, minimal risk of drug-drug interactions, efficient elimination, and low toxicity potential. These findings suggest that furanpydone A is a promising candidate for cancer treatment, warranting further in vitro and in vivo validation, and highlighting its potential impact on the development of new anticancer therapies.

Discovery of novel theophylline derivatives bearing tetrazole scaffold for the treatment of Alzheimer's disease

Alzheimer's disease (AD) is associated with AChE and BACE1 enzymes. Designing inhibitors for preventing these enzymes can be benefit for AD treatment. In this context, theophylline derivatives were generated to prevent the biological activity of AChE and BACE1. In particular, the potential inhibitory of these compounds was rapidly and accurately estimated via knowledge-methods. The in vitro tests were then performed to validate the artificial intelligent approach. Among these, compound 12 exhibited the most potent AChE inhibition with an IC50 of 15.68 μM, while showing limited activity against BACE1. In addition, six compounds were indicated that are able to inhibit AChE, however, the theophylline derivatives play poor performance over the BACE1 target. Atomistic simulations were finally applied to clarify the ligand-binding mechanism to the biological target. The outcomes disclose that theophylline derivatives rigidly form van der Waals interactions to AChE via π-stacking and SC contacts. Overall, the theophylline derivatives may offer a potential scaffold for novel anti-AD agents.

Dynamic Mechanism of Norepinephrine Reuptake and Antidepressants Blockade Regulated by Membrane Potential

During nerve signaling, changes in membrane potential are key to regulating neuronal activity. The norepinephrine transporter (NET) plays a crucial role in the reuptake of norepinephrine (NE), which is essential for maintaining neurotransmitter homeostasis. However, the impact of membrane potential on NET function has long been understudied. Despite the great biological significance of NET, the dynamic molecular mechanisms of NE transport and the blockade effects of antidepressants on this process remain unclear. Here, we reveal the structural, electrostatic, and dynamic characteristics of the NET-NE/antidepressants systems, indicating the dynamic voltage dependence of the NET function. By analyzing the structure and electrostatic properties of the central binding pocket, we find that a hydrophobic network stabilizes the localization of NE, while the dynamic hydrogen bond and salt bridge network plays a crucial role in facilitating the inward transport of NE. Changes in membrane potential significantly affect the reuptake of NE through an electrostatically driven substrate transport pathway, primarily influencing the substrate entrance, the hydrophilic channel leading to the central site, and the exit region. The hyperpolarized state favors NE reuptake, exhibiting a marked preference for inward movement, which aligns with the physiological need for neurons to regulate neurotransmitter concentration in the synaptic cleft via reuptake. Conversely, in the depolarized state, which corresponds to the generation of nerve impulses, NE reuptake may not peak. Furthermore, antidepressants, with their larger molecular size and longer charged amino groups, initially anchor to the essential residue E382 required for NE reuptake. They subsequently occupy the same binding pathway as NE, creating spatial hindrance that effectively blocks NE binding to the central pocket. Additionally, their binding/dissociation behaviors exhibit significant voltage dependence. Under the hyperpolarized state, antidepressants can better block NE entry through more flexible electrostatic and hydrophobic interactions with NET, while the depolarized state raises the binding barrier for antidepressants, facilitating their dissociation. And with this work, a computational strategy for membrane protein-ligand is proposed to emphasize that considering the effects of electric fields in the calculations can reveal more underlying mechanisms and key interactions.

Studying the Signaling Mechanism of Neuropilin-1's Intracellular Disorder Region via Conformational Mining and Dynamic Interaction Characterization

Many single-pass membrane proteins contain an intrinsically disordered region (IDR) within their intracellular domain, playing a key role in regulating cellular signaling. However, understanding the functional mechanisms of these disordered regions has remained a challenge. In this study, we focus on the cytoplasmic IDR of neuropilin-1 (NRP-1 IDR) and employ a combination of experimental and computational methods to investigate its dynamics and function. We compare several enhanced sampling molecular simulations, structural statistics-based methods, and AI-driven conformation mining techniques, emphasizing the strengths and limitations of each with respect to sampling diversity and energy landscape exploration. Subsequently, we investigate the broad array of potential binding partners for the NRP-1 IDR and employ AlphaFold3 for complex structure prediction, highlighting the promiscuous binding behavior of the NRP-1 IDR. Finally, we focus on high-confidence binding partners, GIPC-1 and SNX-5, validating the interaction of the NRP-1 IDR with these proteins and investigating the effects of membrane context and phosphorylation on these interactions. Our findings provide critical insights into how a flexible cytoplasmic region in signal-transmembrane proteins can modulate transmembrane signaling.

Identification of potential inhibitors of Fyn-Kinase from bioactive phytochemicals of Berberis lycium for therapeutic targeting of neurodegenerative disease

Fyn is classified as a member of the Src family of kinases (SFKs), a group of non-receptor tyrosine kinases. It is a critical component of many fundamental central nervous system (CNS) processes. Recently, a connection has been shown between Fyn malfunction and the pathogenic processes exhibited in neurodegenerative conditions, such as Alzheimer's disease (AD), which is a significant factor in worldwide mortality and disability. Due to the rising demographic of elderly individuals, there is a projected increase in incidence of AD in the forthcoming years. This study aims to identify prospective phytochemicals that can be utilized in developing a new protein kinase inhibitor for the therapeutic intervention of AD. The lack of therapeutic interventions capable of preventing the progression of AD is a significant concern thus, it is imperative to identify potential targets. This study employed a virtual screening approach to discover potential Fyn-kinase inhibitors from Berberis lycium (B.ly.) phytoconstituents. Three molecules, Canadine, N-Methyltetrahydroberberine (N-MTHB), and Tetrahydroberberine (THB), were found to have a strong affinity for the binding pocket of Fyn kinase. The docked complexes B.ly. compounds with Fyn underwent all-atom molecular dynamics (MD) simulations to assess their stability and interactions. MD simulation analysis revealed that the identified compounds show promise as potential Fyn inhibitors, which may be implicated in the therapeutic management of AD.

Progress in the discovery and development of anticancer agents from marine cyanobacteria

Covering 2010-April 2024There have been tremendous new discoveries and developments since 2010 in anticancer research based on marine cyanobacteria. Marine cyanobacteria are prolific sources of anticancer natural products, including the tubulin agents dolastatins 10 and 15 which were originally isolated from a mollusk that feeds on cyanobacteria. Decades of research have culminated in the approval of six antibody-drug conjugates (ADCs) and many ongoing clinical trials. Antibody conjugation has been enabling for several natural products, particularly cyanobacterial cytotoxins. Targeting tubulin dynamics has been a major strategy, leading to the discovery of the gatorbulin scaffold, acting on a new pharmacological site. Cyanobacterial compounds with different mechanisms of action (MOA), targeting novel or validated targets in a range of organelles, also show promise as anticancer agents. Important advances include the development of compounds with novel MOA, including apratoxin and coibamide A analogues, modulating cotranslational translocation at the level of Sec61 in the endoplasmic reticulum, largazole and santacruzamate A targeting class I histone deacetylases, and proteasome inhibitors based on carmaphycins, resembling the approved drug carfilzomib. The pipeline extends with SERCA inhibitors, mitochondrial cytotoxins and membrane-targeting agents, which have not yet advanced clinically since the biology is less understood and selectivity concerns remain to be addressed. In addition, efforts have also focused on the identification of chemosensitizing and antimetastatic agents. The review covers the state of current knowledge of marine cyanobacteria as anticancer agents with a focus on the mechanism, target identification and potential for drug development. We highlight the importance of solving the supply problem through chemical synthesis as well as illuminating the biological activity and in-depth mechanistic studies to increase the value of cyanobacterial natural products to catalyze their development.

Design, synthesis, and antitumor evaluation of quinazoline-4-tetrahydroquinoline chemotypes as novel tubulin polymerization inhibitors targeting the colchicine site

We designed, synthesized, and evaluated the antitumor activity of a series of novel quinazoline-4-(6-methoxytetrahydroquinoline) analogues. Among the tested compounds, 4a4 exhibited the most potent antiproliferative activities across four human cancer cell lines with half-maximal inhibitory concentration (IC50) values ranging from 0.4 to 2.7 nM, more potent than the lead compound. The 2.71 Å resolution co-crystal structure of 4a4 with tubulin (PDB code: 8YER) confirmed its critical binding at the colchicine site. Moreover, 4a4 inhibited the polymerization of tubulin, colony formation, and tumor cell migration, while inducing G2/M phase arrest and apoptosis. In vivo, 4a4 significantly delayed primary tumor growth in the SKOV3 xenograft model without obvious side effect. Our research enhances the structure-activity relationships (SARs) understanding of the quinazoline-4-tetrahydroquinoline scaffold and provides new insights for potential structural optimization and the development of novel colchicine binding site inhibitors (CBSIs).

Lipoic acid scaffold applications in the design of multitarget-directed ligands against Alzheimer's disease

Alzheimer's disease (AD) is becoming a fast-growing public health problem which can result in psychological problems as well as loss of speech, language, short-term memory, and motor coordination. Many medications were developed and produced to treat AD, however due to the complexity of the pathology involved in the illness, many of these medications often failed in clinical or preclinical studies. The main issue with the current anti-AD medications is their low efficacy since they use a single target. Multi-target-directed ligands (MTDLs) based on "one molecule; multiple targets" have been introduced to address these two fundamental issues. MTDLs have demonstrated improved efficacy and safety since they regulate many biological targets simultaneously. Alpha-lipoic acid (LA), a natural molecule with distinct properties, is a viable scaffold for developing new MTDLs in treating many neurodegenerative diseases, particularly AD. It is a key mitochondrial enzymes' cofactor and an organic molecule with disulfide functionality. It also has potent antioxidant characteristics that enhance mitochondrial activity. Considering the neuroprotective and anti-inflammatory effects of LA, various hybrids of LA with tacrine, rivastigmine, coumarin and chromone, ibuprofen, melatonin, niacin have been synthesized and biologically evaluated as the MTDLs. In this article, we review the design of LA-based hybrids or conjugates, their biological activities, and structure-activity relationship studies, to develop new MTDLs in the field of AD pharmacotherapy.

Sulforaphane suppresses Aβ accumulation and tau hyperphosphorylation in vascular cognitive impairment(VCI)

Sulforaphane (Sfn) is a compound naturally found in cruciferous vegetables such as broccoli, Brussels sprouts, cabbage, and kale. It is well-known for its antioxidative and anti-inflammatory effects. Sfn has attracted attention for its potential health benefits, particularly its role in brain health and the potential prevention of dementia and neurodegeneration. Alzheimer's disease (AD) and vascular cognitive impairment (VCI) are the top two causes of dementia. Cerebral vascular lesions give rise to VCI and predispose neurons to degeneration and Alzheimer's disease (AD) by Aβ accumulation and tau hyperphosphorylation. In a rat model of VCI by permanent bilateral common carotid artery occlusion (2VO), we tested the protective effect of the phase II enzyme inducer sulforaphane (Sfn). Sfn ameliorates vascular cognitive deficits by reducing the typical white matter injury and neural atrophy pathological changes in VCI. Moreover, for the first time, we demonstrated that it effectively reduced Aβ and toxic p-tau accumulation in VCI. The protective mechanisms of Sfn involve the induction of HO-1 expression, activation of the Akt/GSK3β pathway, and modulation of amyloid precursor protein (APP) expression levels. Our data suggest that Sfn is a promising therapeutic compound to treat VCI and AD. It inhibits short-term neuron and white matter injuries as well as long-term Aβ and p-tau accumulation caused by cerebral vascular lesions.

Discovery of a novel DYRK1A inhibitor with neuroprotective activity by virtual screening and in vitro biological evaluation

Dual-specificity tyrosine phosphorylation-regulated kinase 1A (DYRK1A) is implicated in accumulation of amyloid β-protein (Aβ) and phosphorylation of Tau proteins, and thus represents an important therapeutic target for neurodegenerative diseases. Though many DYRK1A inhibitors have been discovered, there is still no marketed drug targeting DYRK1A. This is partly due to the lack of effective and safe chemotypes. Therefore, it is still necessary to identify new classes of DYRK1A inhibitors. By performing virtual screening with the workflow mainly composed of pharmacophore modeling and molecular docking as well as the following DYRK1A inhibition assay, we identified compound L9, ((Z)-1-(((5-phenyl-1H-pyrazol-4-yl)methylene)-amino)-1H-tetrazol-5-amine), as a moderately active DYRK1A inhibitor (IC50: 1.67 μM). This compound was structurally different from the known DYRK1A inhibitors, showed a unique binding mode to DYRK1A. Furthermore, compound L9 showed neuroprotective activity against okadaic acid (OA)-induced injury in the human neuroblastoma cell line SH-SY5Y by regulating the expression of Aβ and phosphorylation of Tau protein. This compound was neither toxic to the SH-SY5Y cells nor to the human normal liver cell line HL-7702 (IC50: >100 μM). In conclusion, we have identified a novel DYRK1A inhibitor with neuroprotective activity through virtual screening and in vitro biological evaluation, which holds the promise for further study.

Leveraging the Thermodynamics of Protein Conformations in Drug Discovery

As the name implies, structure-based drug design requires confidence in the holo complex structure. The ability to clarify which protein conformation to use when ambiguity arises would be incredibly useful. We present a large scale validation of the computational method Protein Reorganization Free Energy Perturbation (PReorg-FEP) and demonstrate its quantitative accuracy in selecting the correct protein conformation among candidate models in apo or ligand induced states for 14 different systems. These candidate conformations are pulled from various drug discovery related campaigns: cryptic conformations induced by novel hits in lead identification, binding site rearrangement during lead optimization, and conflicting structural biology models. We also show an example of a pH-dependent conformational change, relevant to protein design.

Fyn Kinase in Alzheimer's Disease: Unraveling Molecular Mechanisms and Therapeutic Implications

Alzheimer's disease, characterized by the accumulation of abnormal protein aggregates and neuronal damage in the brain, leads to a gradual decline in cognitive function and memory. As a complex neurodegenerative disorder, it involves disruptions in various biochemical pathways and neurotransmitter systems, contributing to the progressive loss of neurons and synaptic connections. The complexity of Alzheimer's signaling pathways complicates treatment, presenting a formidable challenge in the quest for effective therapeutic interventions. A member of the Src family of kinases (SFKs), Fyn, is a type of non-receptor tyrosine kinase that has been linked to multiple essential CNS processes, such as myelination and synaptic transmission. Fyn is an appealing target for AD treatments because it is uniquely linked to the two major pathologies in AD by its interaction with tau, in addition to being activated by amyloid-beta (Aβ) through PrPC. Fyn mediates neurotoxicity and synaptic impairments caused by Aβ and is involved in regulating the process of Aβ synthesis.Additionally, the tau protein's tyrosine phosphorylation is induced by Fyn. Fyn is also a challenging target because of its widespread body expression and strong homology with other kinases of the Src family, which could cause unintentional off-target effects. This review emphasizes signaling pathways mediated by Fyn that govern neuronal development and plasticity while also summarizing the most noteworthy recent research relevant to Fyn kinase's function in the brain. Additionally, the therapeutic inhibition of Fyn kinase has been discussed, with a focus on the Fyn kinase inhibitors that are in clinical trials, which presents a fascinating opportunity for targeting Fyn kinase in the creation of possible therapeutic approaches for the management of Alzheimer's disease.

Promising tools for future drug discovery and development in antiarrhythmic therapy

Arrhythmia refers to irregularities in the rate and rhythm of the heart, with symptoms spanning from mild palpitations to life-threatening arrhythmias and sudden cardiac death. The complex molecular nature of arrhythmias complicates the selection of appropriate treatment. Current therapies involve the use of antiarrhythmic drugs (class I-IV) with limited efficacy and dangerous side effects and implantable pacemakers and cardioverter-defibrillators with hardware-related complications and inappropriate shocks. The number of novel antiarrhythmic drugs in the development pipeline has decreased substantially during the last decade and underscores uncertainties regarding future developments in this field. Consequently, arrhythmia treatment poses significant challenges, prompting the need for alternative approaches. Remarkably, innovative drug discovery and development technologies show promise in helping advance antiarrhythmic therapies. In this article, we review unique characteristics and the transformative potential of emerging technologies that offer unprecedented opportunities for transitioning from traditional antiarrhythmics to next-generation therapies. We assess stem cell technology, emphasizing the utility of innovative cell profiling using multiomics, high-throughput screening, and advanced computational modeling in developing treatments tailored precisely to individual genetic and physiological profiles. We offer insights into gene therapy, peptide, and peptibody approaches for drug delivery. We finally discuss potential strengths and weaknesses of such techniques in reducing adverse effects and enhancing overall treatment outcomes, leading to more effective, specific, and safer therapies. Altogether, this comprehensive overview introduces innovative avenues for personalized rhythm therapy, with particular emphasis on drug discovery, aiming to advance the arrhythmia treatment landscape and the prevention of sudden cardiac death. SIGNIFICANCE STATEMENT: Arrhythmias and sudden cardiac death account for 15%-20% of deaths worldwide. However, current antiarrhythmic therapies are ineffective and have dangerous side effects. Here, we review the field of arrhythmia treatment underscoring the slow progress in advancing the cardiac rhythm therapy pipeline and the uncertainties regarding evolution of this field. We provide information on how emerging technological and experimental tools can help accelerate progress and address the limitations of antiarrhythmic drug discovery.

Toxoplasma replication is inhibited by MMV676477 without development of resistance

Protozoan parasites cause life-threatening infections in both humans and animals, including agriculturally significant livestock. Available treatments are typically narrow spectrum and are complicated by drug toxicity and the development of resistant parasites. Protozoan tubulin is an attractive target for the development of broad-spectrum antimitotic agents. The Medicines for Malaria Pathogen Box compound MMV676477 was previously shown to inhibit replication of kinetoplastid parasites, such as Leishmania amazonensis and Trypanosoma brucei, and the apicomplexan parasite Plasmodium falciparum by selectively stabilizing protozoan microtubules. In this report, we show that MMV676477 inhibits intracellular growth of the human apicomplexan pathogen Toxoplasma gondii with an EC50 value of ~50 nM. MMV676477 does not stabilize vertebrate microtubules or cause other toxic effects in human fibroblasts. The availability of tools for genetic studies makes Toxoplasma a useful model for studies of the cytoskeleton. We conducted a forward genetics screen for MMV676477 resistance, anticipating that missense mutations would delineate the binding site on protozoan tubulin. Unfortunately, we were unable to use genetics to dissect target interactions because no resistant parasites emerged. This outcome suggests that future drugs based on the MMV676477 scaffold would be less likely to be undermined by the emergence of drug resistance.

Estimating AChE inhibitors from MCE database by machine learning and atomistic calculations

Acetylcholinesterase (AChE) is one of the most successful targets for the treatment of Alzheimer's disease (AD). Inhibition of AChE can result in preventing AD. In this context, the machine-learning (ML) model, molecular docking, and molecular dynamics calculations were employed to characterize the potential inhibitors for AChE from MedChemExpress (MCE) database. The trained ML model was initially employed for estimating the inhibitory of MCE compounds. Atomistic simulations including molecular docking and molecular dynamics simulations were then used to confirm ML outcomes. In particular, the physical insights into the ligand binding to AChE were clarified over the calculations. Two compounds, PubChem ID of 130467298 and 132020434, were indicated that they can inhibit AChE.

Synthesis of novel imino-coumarin and acrylonitrile 2-benzazole hybrids as potent anticancer agents targeting tubulin

Building on previous research indicating the robust biological effects of coumarins, we focused on exploring imino-coumarin 2-benzazole conjugates. Compounds were tested for antiproliferative activity in vitro, with the most active ones further examined to determine the mechanism of biological action. Five derivatives exhibited significant antiproliferative activity against all tested cancer cells (IC50 ranging from 0.04 to 8.5 μM), falling within the low micromolar/submicromolar range of inhibitory concentrations. Three compounds had remarkable antiproliferative effects against Capan-1 (IC50 0.04-0.05 μM) and DND-41 (IC50 0.06-0.07 μM). Promising compounds were further investigated, confirming their mechanism of action through tubulin polymerization inhibition. Computational docking and molecular dynamics simulations confirmed the high affinity of potent derivatives for the tubulin colchicine site and justified the suitability of the employed skeleton by identifying crucial protein-ligand interactions promoting binding. This insight highlights a strategy for further potency improvements through substituents that can donate hydrogen bonds or bear a positive charge, allowing such ligands to more optimally adapt to the identified anionic binding site environment.

Dual-targeting inhibitors involving tubulin for the treatment of cancer

Combination therapies play a pivotal role in cancer treatment due to the intricate nature of the disease. Tubulin, a protein crucial for cellular functions, is a prime target in tumor therapy as it regulates microtubule dynamics. Combining tubulin inhibitors with other different inhibitors as dual targeting inhibitors has shown synergistic anti-tumor effects, amplifying therapeutic outcomes. Despite clinical approval of several tubulin inhibitors, their efficacy is hampered by drug resistance and toxic side effects. Dual targeting inhibitors of tubulin and other cancer-related pathways have emerged as vital components in cancer therapy, with promising prospects in both market availability and ongoing clinical trials. The rational design of hybrid inhibitors targeting both pathways presents an innovative approach to combatting cancer. However, despite the potent anti-tumor activity exhibited by several compounds, research on their anti-angiogenic potential remains limited. This review emphasizes the significance of tubulin based dual-target inhibitors, elucidating their mechanisms of action. Recent advances in exploring therapeutic efficacy, toxicity profiles, and challenges such as MDR are discussed. By presenting the research progress of tubulin based dual-target inhibitors as potential anticancer agents, this study delivers valuable insights for the development of more efficient drugs for cancer therapy.

Detection of Putative Ligand Dissociation Pathways in Proteins Using Site-Identification by Ligand Competitive Saturation

Drug efficacy often correlates better with dissociation kinetics than binding affinity alone. To study binding kinetics computationally, it is necessary to identify all of the possible ligand dissociation pathways. The site identification by ligand competitive saturation (SILCS) method involves the precomputation of a set of maps (FragMaps), which describe the free energy landscapes of typical chemical functionalities in and around a target protein or RNA. In the current work, we present and implement a method to use SILCS to identify ligand dissociation pathways, termed "SILCS-Pathway." The A* pathfinding algorithm is utilized to enumerate ligand dissociation pathways between the ligand binding site and the surrounding bulk solvent environment defined on evenly spaced points around the protein based on a Fibonacci lattice. The cost function for the A* algorithm is calculated using the SILCS exclusion maps and the SILCS grid free energy scores, thereby identifying paths that account for local protein flexibility and potential favorable interactions with the ligand. By traversing all evenly distributed bulk solvent points around the protein, we located all possible dissociation pathways and clustered them to identify general ligand unbinding pathways. The procedure is verified by using proteins studied previously with enhanced sampling molecular dynamics (MD) techniques and is shown to be capable of capturing important ligand dissociation routes in a highly computationally efficient manner. The identified pathways will act as the foundation for determining ligand dissociation kinetics using SILCS free energy profiles, which will be described in a subsequent article.

A structural phylogenetic tree of Rad52 and its annealase superfamily

Rad52, a highly conserved eukaryotic protein, plays a crucial role in DNA repair, particularly in double-strand break repair. Recent findings reveal that its distinct structural features, including a characteristic β-sheet and β-hairpin motif, are shared with the lambda phage single-strand annealing protein, Redβ, and other prokaryotic single-strand annealing proteins (SSAPs), indicating a common superfamily. Our analysis of over 10,000 SSAPs across all domains of life supports this hypothesis, confirming the presence of the characteristic motif despite variations in size and composition. We found that archaea, representing only 1% of the studied proteins, exhibit most of these variations as reflected by their spread across the phylogenetic tree, whereas eukaryotes exhibit only Rad52. By examining four representative archaeal SSAPs, we elucidate the structural relationship between eukaryotic and bacterial SSAPs, highlighting differences in β-sheet size and β-hairpin complexity. Furthermore, we identify an archaeal SSAP with a predicted structure nearly identical to human Rad52. Together with a screen of over 100 million unannotated proteins for potential SSAP candidates, our computational analysis complements the existing sequence and structural evidence supporting orthology among five SSAP families: Rad52, Redβ, RecT, Erf, and Sak3.

DNA protection, molecular docking, molecular dynamic, enzyme inhibition, and kinetics studies of apigenin isolated from Nepeta baytopii Hedge & Lamond by bioactivity-guided fractionation

Plant-derived bioactive substances have demonstrated significant qualities that suggest they may be crucial in preventing various chronic diseases. Flavonoids, which include apigenin, are the biggest group of polyphenols. In our study, we aimed to obtain the methanol-chloroform (1:1) extract from the aerial parts of Nepeta baytopii Hedge & Lamond and purify the apigenin using bioactivity-guided isolation to separate the active fraction. The current in vitro study provides updated knowledge on apigenin regarding its previously unresearched DNA protection activity and enzyme inhibition, enzyme inhibition kinetics, and enzyme-apigenin interactions. In this context, these studies will be the first and will contribute to the literature. Apigenin had high urease (IC50-5.00 ± 0.00 µM), butyrlcholinesterase (BChE:IC50-10.48 ± 0.00 µM), and tyrosinase (IC50-177.82 ± 14.40 µM) inhibition activities, while inhibition binding constants were high in urease (Ki-0.05 mM), tyrosinase (Ki-0.06 mM), and carbonic anhydrase (Ki-0.08 mM). The binding affinities and constants of the interaction were also ascertained to be high for BChE (-9.50 kcal/mol, and Ki-0.11 µM), and tyrosinase (-8.80 kcal/mol, and Ki, 0.62 µM) with apigenin. In summary, apigenin can be used as an inhibitor for five enzymes. These results will give priority to further studies. Apigenin showed high DNA protection activity with a Form I value of 67.37%. These data demonstrated that the interaction formed by BChE-apigenin gave the best results regarding enzyme inhibition and enzyme-molecule interaction. The stability of this complex was evaluated using molecular dynamics modeling.

Discovery of novel quinazoline derivatives as tubulin polymerization inhibitors targeting the colchicine binding site with potential anti-colon cancer effects

Tubulin is a critical target for cancer therapy, with colchicine binding site inhibitors (CBSIs) being the most extensively researched. A series of quinazoline derivatives designed to target the colchicine binding site of tubulin were synthesized and evaluated for their biological activities. The antiproliferative effects of these compounds were tested against six human cancer cell lines, and compound Q19 demonstrated potent antiproliferative activity against the HT-29 cell line, with an IC50 value of 51 nM. Additionally, further investigation revealed that Q19 effectively inhibited microtubule polymerization by binding to the colchicine binding site on tubulin. Furthermore, compound Q19 arrested the HT-29 cell cycle at the G2/M phase, induced apoptosis in these cells, and disrupted angiogenesis. Finally, compound Q19 exhibited potent inhibitory effects on tumor growth in HT-29 xenografted mice while demonstrating minimal toxic side effects and acceptable pharmacokinetic properties. These findings suggested that Q19 hold promise as a potential candidate for colon cancer therapy targeting tubulin.

Prioritizing Parkinson's disease risk genes in genome-wide association loci

Recent advancements in Parkinson's disease (PD) drug development have been significantly driven by genetic research. Importantly, drugs supported by genetic evidence are more likely to be approved. While genome-wide association studies (GWAS) are a powerful tool to nominate genomic regions associated with certain traits or diseases, pinpointing the causal biologically relevant gene is often challenging. Our aim was to prioritize genes underlying PD GWAS signals. The polygenic priority score (PoPS) is a similarity-based gene prioritization method that integrates genome-wide information from MAGMA gene-level association tests and more than 57,000 gene-level features, including gene expression, biological pathways, and protein-protein interactions. We applied PoPS to data from the largest published PD GWAS in East Asian- and European-ancestries. We identified 120 independent associations with P < 5×10-8 and prioritized 46 PD genes across these loci based on their PoPS scores, distance to the GWAS signal, and presence of non-synonymous variants in the credible set. Alongside well-established PD genes (e.g., TMEM175 and VPS13C), some of which are targeted in ongoing clinical trials (i.e., SNCA, LRRK2, and GBA1), we prioritized genes with a plausible mechanistic link to PD pathogenesis (e.g., RIT2, BAG3, and SCARB2). Many of these genes hold potential for drug repurposing or novel therapeutic developments for PD (i.e., FYN, DYRK1A, NOD2, CTSB, SV2C, and ITPKB). Additionally, we prioritized potentially druggable genes that are relatively unexplored in PD (XPO1, PIK3CA, EP300, MAP4K4, CAMK2D, NCOR1, and WDR43). We prioritized a high-confidence list of genes with strong links to PD pathogenesis that may represent our next-best candidates for disease-modifying therapeutics. We hope our findings stimulate further investigations and preclinical work to facilitate PD drug development programs.

Discovery and biological evaluation of 6-aryl-4-(3,4,5-trimethoxyphenyl)quinoline derivatives with promising antitumor activities as novel colchicine-binding site inhibitors

Tubulin, as the fundamental unit of microtubules, is a crucial target in the investigation of anticarcinogens. The synthesis and assessment of small-molecule tubulin polymerization inhibitors remains a promising avenue for the development of novel cancer therapeutics. Through an analysis of reported colchicine-binding site inhibitors (CBSIs) and tubulin binding models, a set of 6-aryl-4-(3,4,5-trimethoxyphenyl)quinoline derivatives were meticulously crafted as potential CBSIs. Notably, compound 14u exhibited potent anti-proliferative efficacy, displaying IC50 values ranging from 0.03 to 0.18 μM against three human cancer cell lines (Huh7, MCF-7, and SGC-7901). Mechanistic investigations revealed that compound 14u could disrupt tubulin polymerization, dismantle the microtubule architecture, arrest the cell cycle at G2/M phase, and induce apoptosis in cancer cells. Furthermore, compound 14u demonstrated significant inhibition of tumor proliferation in vivo with no discernible toxicity in the Huh7 orthotopic tumor model mice. Additionally, physicochemical property predictions indicated that compound 14u adhered well to Lipinski's rule of five. These findings collectively suggest that compound 14u holds promise as an antitumor agent targeting the colchicine-binding site on tubulin and warrants further investigation.

Targeting serotonin receptors with phytochemicals - an in-silico study

The potential of natural phytochemicals in mitigating depression has been supported by substantial evidence. This study evaluated a total of 88 natural phytochemicals with potential antidepressant properties by targeting serotonin (5-HT) receptors (5-HT1A, 5-HT4, and 5-HT7) using molecular docking, ADMET (Absorption, Distribution, Metabolism, Excretion, and Toxicity) analysis, internal coordinates normal mode analysis (NMA), molecular dynamics simulation (MDS), and free energy calculation. Five evaluated compounds (Genistein, Kaempferol, Daidzein, Peonidin, and glycitein) exhibited favorable pharmacokinetic properties and improved binding scores, indicating their potential as effective antidepressants. Redocking and superimposition analysis of 5-HT with cocrystal structures validated these findings. Furthermore, NMA, MDS, and free energy calculations confirmed the stability and deformability of the ligand-receptor complexes, suggesting that these phytochemicals can effectively interact with 5-HT receptors to modulate depressive symptoms. These powerful phytochemicals, abundantly found in soybeans, fruits, vegetables, and herbs, represent a promising avenue for developing natural treatments for depression. Further in vitro and in vivo studies are warranted to explore their efficacy in alleviating stress and depression through their interactions with 5-HT receptors.

An in-silico approach to target multiple proteins involved in anti-microbial resistance using natural compounds produced by wild mushrooms

Bacterial resistance to antibiotics and the number of patients infected by multi-drug-resistant bacteria have increased significantly over the past decade. This study follows a computational approach to identify potential antibacterial compounds from wild mushrooms. Twenty-six known compounds produced by wild mushrooms were docked to assess their affinity with drug targets of antibiotics such as penicillin-binding protein-1a (PBP1a), DNA gyrase, and isoleucyl-tRNA synthetase (ILERS). Docking scores were further validated by multiple receptor conformer (MRC)-based docking studies. Based on the MRC-based docking results, eight molecules were shortlisted for ADMET analysis. Molecular dynamics (MD) simulations were further performed to evaluate the conformational stability of the ligand-protein complexes. Binding energies were computed by the gmx_MMPBSA method. The data were obtained in terms of root-mean square deviation, and root-mean square fluctuation justified the stability of Austrocortilutein A, Austrocortirubin, and Confluentin in complex with several proteins under physiological conditions. Among these, Austrocortilutein A displayed better binding affinity with PBP1a and ILERS when compared with their respective reference ligands. This study is preliminary and aims to help drive the search for compounds that have the capacity to overcome the anti-microbial resistance of prevalent bacteria, using natural compounds produced by wild mushrooms. Further experimental validation is required to justify the clinical use of the studied compounds.

Enhancing therapeutic efficacy in homologous recombination-proficient pancreatic cancer via the combination of PARP1-PROTAC and a BRD4 inhibitor

Currently, poly (ADP-ribose) polymerase inhibitors (PARPi) have been approved by U.S. Food and Drug Administration for BRCA-mutated pancreatic cancer therapy. However, limited indications hinder their further application. Repression of bromodomain-containing protein 4 (BRD4) can block the homologous recombination (HR) repair pathway and has the potential to enhance the response to PARPi in HR-proficient pancreatic cancer therapy. In addition, proteolysis targeting chimeras (PROTACs) can hijack E3 ligase within the cell to ubiquitinate degradation-targeted proteins effectively and quickly, thus enhancing the therapeutic effect on tumors. In the present study, the LB23 compound, which induces PARP1 degradation, was employed in combination with the BRD4 inhibitor JQ1, confirming their synergistic effect in HR-proficient pancreatic cancer through various methods. Moreover, compared to the JQ1 and PARPi olaparib combination, PARP1-PROTAC and JQ1 had more notable synergistic effects. Further research into the synergistic mechanism demonstrated that combination therapy enhanced DNA damage and suppressed DNA repair by inducing cell cycle arrest and cell apoptosis. The present study therefore provides the experimental data for this type of combination therapy, which is expected to be an innovative approach for the treatment of HR-proficient pancreatic cancer.

Ex-vivo antioxidant, enzyme inhibitory properties and computational analysis unveil the molecular mechanism of cardiac and penile phosphodiesterase-5 inhibition by bacterial strain HOKA1 extract as an aphrodisiac's agent

The study uses in-vitro antioxidant, ex-vivo enzyme kinetics and in-silico approach using standard protocols to understand their inhibitory mechanism better. The study revealed that bacterial strain HOKA1 isolated from Oniru beach, grown in nutrient agar supplemented with sodium chloride (30%NaCl). Moreso, the bacterial strain HOKA1 extract showed better antioxidant capability and greatly reduced the penile and cardiac cGMP with the highest penile and cardiac concentration between 0.013 and 0.183 μM/Min as compared to the sildenafil citrate (0.00-0.203 μM/Min). Moreover, the kinetic parameters (Vmax and Km) effects revealed that bacterial strain HOKA1 extract inhibited PDE-5 activities better than sildenafil citrate. The GC-MS analysis revealed twenty-nine bioactive compounds in the extract, and these compounds could provide comprehensible supporting evidence for the antioxidant and inhibitory potential of the strain HOKA1 extract on PDE-5 activity. Molecular docking study revealed majority of the GC-MS-identified bioactive constituents from the HOKA1 extract showed high binding energy or lower bonding affinities (-6.8 to -3.3 kcal/mol) compared to reference drug sildenafil citrate (-9.6 kcal/mol), except campesterol (-10.0 kcal/mol); also, ergostane (-9.9 kcal/mol). The results of 100 ns simulation (RMSF, RMSD, Rg and H-bond) show extraordinary stability of PDE-5 with campesterol and ergostane, so also complimentary binding energy of MM-PBSA (campesterol -65.92±4.09 kcal/mol; ergostane -57.23±4.70 kcal/mol) indicating their probability of acting promising PDE-5 inhibitors. Therefore, the study revealed that bacterial strain HOKA1 extract showed a better aphrodisiac property, and its bioactive compounds (campesterol and ergostane) should be considered in upcoming rational development and design of more active selective PDE-5 inhibitors, making a treatment for erectile dysfunction.

Design, synthesis, and evaluation of novel stilbene derivatives that degrade acidic nucleoplasmic DNA-binding protein 1 (And1) and synergize with PARP1 inhibitor in NSCLC cells

Specifically inducing the degradation of acidic nucleoplasmic DNA-binding protein 1 (And1) is a promising antitumor strategy. Our previous study identified Bazedoxifene (BZA) and CH3 as specific And1 degraders and validated their activity in reversing radiotherapy resistance in vitro and in vivo. However, unelucidated structure-activity relationships and moderate activity have limited their application. In this study, 27 novel CH3 derivatives were designed and synthesised based on the cavity topology of the WD40 domain of And1. Among them, A15 with a "V" conformation significantly induced And1 degradation in NSCLC cells. In addition, this study demonstrated a potential synthetic lethal effect of And1 degraders and PARP1 inhibitors. 1 µM of Olaparib in combination with 5 µM of A15 significantly inhibited the proliferation of A549 and H460 cells. Overall, these compounds are valuable tools for elucidating And1 biology, and their special spatial conformation make them promising candidates for future optimisation studies.

Copper-assisted anticancer activity of hydroxycinnamic acid terpyridine conjugates on triple-negative breast cancer

The development of active therapeutic agents to treat highly metastatic cancer while minimizing damage to healthy cells is of utmost importance. Due to potential antioxidant properties, hydroxycinnamic acid derivatives (caffeic acid and p-coumaric acids) were found to inhibit highly metastatic breast cancer cell growth both in vitro and in vivo without much effect on normal cells. Especially due to the structure-activity relationships, ester and amide derivatives of hydroxycinnamic acids are reported to gain much higher radical scavenging ability than their naked hydroxycinnamic acid analogs like caffeic acid and p-coumaric acid. These results prompted us to design a set of ligands by incorporating an amide moiety on caffeic acid and p-coumaric acid to achieve the least toxicity towards healthy cell lines. Further, the Cu(II) complexes of amide-coupled caffeic acid and p-coumaric acid ligands have been explored for their therapeutic activity on triple-negative breast cancer and other cancer cells like colon, and prostate cancer. The Cu(II) complexes (4 & 5) were characterized by UV-Vis spectroscopy, FTIR, and X-band EPR spectroscopy. The trigonal bipyramidal geometry of complexes was confirmed by the X-band EPR spectra recorded in solution state at liquid N2 temperature. The purity of the complexes was determined by elemental analysis and HPLC traces. Initially, Calf thymus DNA (ct-DNA) binding studies with the complexes were explored. The results suggested the complexes (4 & 5) bind majorly through an intercalative mode of binding with ct-DNA, whereas no significant binding was observed for the bare organic ligands (2 & 3). The intercalation binding modes of 4 and 5 were further supported by UV-visible spectroscopy, ct-DNA melting point analysis, and CD spectroscopy. Moreover, these complexes showed better activity towards cisplatin-resistant TNBC cell lines (4T1, a TNBC cell line derived from the mammary gland tissue of a mouse). The combination of antioxidants and Cu(II) as the metal center made the complexes more cytotoxic toward cancer cell lines (4T1) (IC50 ∼ 3.5 ± 2.5 μM) and the least toxic toward healthy cells (L929) (IC50 ∼ 15 ± 5 μM). Finally, the mechanism of cell death was studied using JC-1 staining and a cell colony formation assay. These studies might help in designing safer anticancer drugs for treating more aggressive types of cancer.

Galantamine-Memantine Combination in the Treatment of Parkinson's Disease Dementia

Parkinson's disease (PD) is a progressive neurodegenerative disorder that affects over 1% of population over age 60. It is defined by motor and nonmotor symptoms including a spectrum of cognitive impairments known as Parkinson's disease dementia (PDD). Currently, the only US Food and Drug Administration-approved treatment for PDD is rivastigmine, which inhibits acetylcholinesterase and butyrylcholinesterase increasing the level of acetylcholine in the brain. Due to its limited efficacy and side effect profile, rivastigmine is often not prescribed, leaving patients with no treatment options. PD has several derangements in neurotransmitter pathways (dopaminergic neurons in the nigrostriatal pathway, kynurenine pathway (KP), acetylcholine, α7 nicotinic receptor, and N-methyl-D-aspartate (NMDA) receptors) and rivastigmine is only partially effective as it only targets one pathway. Kynurenic acid (KYNA), a metabolite of tryptophan metabolism, affects the pathophysiology of PDD in multiple ways. Both galantamine (α7 nicotinic receptor) and memantine (antagonist of the NMDA subtype of the glutamate receptor) are KYNA modulators. When used in combination, they target multiple pathways. While randomized controlled trials (RCTs) with each drug alone for PD have failed, the combination of galantamine and memantine has demonstrated a synergistic effect on cognitive enhancement in animal models. It has therapeutic potential that has not been adequately assessed, warranting future randomized controlled trials. In this review, we summarize the KYNA-centric model for PD pathophysiology and discuss how this treatment combination is promising in improving cognitive function in patients with PDD through its action on KYNA.

Combining de novo molecular design with semiempirical protein-ligand binding free energy calculation

Semi-empirical quantum chemistry methods estimate the binding free energies of protein-ligand complexes. We present an integrated approach combining the GFN2-xTB method with de novo design for the generation and evaluation of potential inhibitors of acetylcholinesterase (AChE). We employed chemical language model-based molecule generation to explore the synthetically accessible chemical space around the natural product Huperzine A, a potent AChE inhibitor. Four distinct molecular libraries were created using structure- and ligand-based molecular de novo design with SMILES and SELFIES representations, respectively. These libraries were computationally evaluated for synthesizability, novelty, and predicted biological activity. The candidate molecules were subjected to molecular docking to identify hypothetical binding poses, which were further refined using Gibbs free energy calculations. The structurally novel top-ranked molecule was chemically synthesized and biologically tested, demonstrating moderate micromolar activity against AChE. Our findings highlight the potential and certain limitations of integrating deep learning-based molecular generation with semi-empirical quantum chemistry-based activity prediction for structure-based drug design.

An update on small molecule compounds targeting synthetic lethality for cancer therapy

Targeting cancer-specific vulnerabilities through synthetic lethality (SL) is an emerging paradigm in precision oncology. A SL strategy based on PARP inhibitors has demonstrated clinical efficacy. Advances in DNA damage response (DDR) uncover novel SL gene pairs. Beyond BRCA-PARP, emerging SL targets like ATR, ATM, DNA-PK, CHK1, WEE1, CDK12, RAD51, and RAD52 show clinical promise. Selective and bioavailable small molecule inhibitors have been developed to induce SL, but optimization for potency, specificity, and drug-like properties remains challenging. This article illuminated recent progress in the field of medicinal chemistry centered on the rational design of agents capable of eliciting SL specifically in neoplastic cells. It is envisioned that innovative strategies harnessing SL for small molecule design may unlock novel prospects for targeted cancer therapeutics going forward.

Revealing binding mechanism of β-casein to chrysin, apigenin, and luteolin and locating its binding pockets by molecular docking and molecular dynamics

Revealing the interaction mechanism of proteins with bioactive molecules and the location of their binding pockets is crucial for predicting the structure-function relationship of proteins in drug discovery and design. Despite some published papers on the interaction of β-casein with small bioactive molecules, the ambiguity of the location and constituent amino acids of β-casein binding pockets prompted us to identify them by in silico simulation of its interaction with three polyphenols, chrysin, apigenin, and luteolin. Molecular docking revealed that the primary β-casein binding pocket for chrysin consists of five nonpolar amino acids (Leu73, Phe77, Pro80, Ile89, and Pro196), three polar neutral amino acids (Ser137, Gln138, and Gln197), and two polar charged amino acids (Glu136, and Arg198). For β-casein/apigenin and β-casein/luteolin complexes, Asn83 also contributes to forming the pocket. Molecular dynamics provided more details, such as the relative contribution of determinative amino acids and the role of various forces. For example, we found that Glu210, Glu132, and Glu35 are the most destructive residues in the binding of chrysin, apigenin, and luteolin to β-casein, respectively. Also, we observed that hydrophobic forces mainly stabilize β-casein/chrysin and β-casein/apigenin, and polar solvation (including hydrogen bonds) stabilizes β-casein/luteolin, all by spontaneous processes.

In silico discovery of druggable targets in Citrobacter koseri using echinoderm metabolites and molecular dynamics simulation

Citrobacter koseri causes infection in people who are immunocompromised. Without effective antibiotics, these infections can become severe and life-threatening, so effective drugs are essential to treat these infections. Utilizing subtractive genomics, 2699 ORFs were predicted and translated into amino acid sequences. Metabolic pathway analysis and subcellular localization helped define the roles of key bacterial proteins. Two druggable proteins, WP_012000829.1 and WP_275157394.1, were discovered as promising targets. Alpha Fold provided 3D structures, and a library of 1600 echinoderm metabolites was docked against these proteins, with Ampicillin, Levofloxacin, and Doxycycline as controls. Notably, CMNPD13085 and CMNPD15632 exhibited the highest binding affinities for WP_012000829.1 and WP_275157394.1, respectively. Molecular dynamics simulations and MM-GBSA binding free energy complemented docking results. However, acknowledging the reliance on computational validations, the study emphasizes the need for essential in-vitro research to transform these potential inhibitors into therapeutic drugs.

A molecular dynamics simulations analysis of repurposing drugs for COVID-19 using bioinformatics methods

A number of multidisciplinary methods have piqued the interest of researchers as means to accelerate and lower the cost of medication creation. The goal of this research was to find target proteins and then select a lead drug against SARS-CoV-2. The three-dimensional structure is taken from the RCSB PDB using its specific PDB ID 6lu7. Virtual screening based on pharmacophores is performed using Molecular Operating Environment software. We looked for a potent inhibitor in the FDA-approved database. For docking, AutoDock Vina uses Pyrx. The compound-target protein binding interactions were tested using BIOVIA Discovery Studio. The stability of protein and inhibitor complexes in a physiological setting was investigated using Desmond's Molecular Dynamics Simulation (MD simulation). According to our findings, we repurpose the FDA-approved drugs ZINC000169677008 and ZINC000169289767, which inhibit the activity of the virus's main protease (6lu7). The scientific community will gain from this finding, which might create new medicine. The novel repurposed chemicals were promising inhibitors with increased efficacy and fewer side effects.Communicated by Ramaswamy H. Sarma.

Effect of isoproterenol, a β-adrenergic agonist, on the differentiation of insulin-producing pancreatic β cells derived from human pluripotent stem cells

Research on islet replacement through the differentiation of functionally matured insulin-producing β-like cells for the treatment of diabetes presents a significant challenge. Neural signals in β cell differentiation significantly impact the pancreatic microenvironment in glucose metabolism, but they are not fully understood. In this study, isoproterenol, a β adrenoreceptor agonist, was introduced into pancreatic progenitor cells, derived from human pluripotent stem cells in vitro, undergoing endocrine differentiation, using 2-dimensional (2D) and 3-dimensional (3D) differentiation protocols. This resulted in increased insulin and C-peptide secretion, along with elevated expression of key pancreatic beta cell transcription factors, including PDX-1, NKX6.1, and MAFA, and improved function, demonstrated by increased responsiveness to glucose determined via a glucose-stimulated insulin secretion test. Moreover, RNA transcriptome analysis of isoproterenol-treated endocrine progenitors facilitated the identification of biological pathways and genes that contribute to mature beta cell differentiation efficiency correlated with neural signals, such as adrenoceptor beta 1, calcium/calmodulin dependent protein kinase II alpha, phospholipase C delta 4, and neurotrophic receptor tyrosine kinase 1. Among those genes, calcium/calmodulin dependent protein kinase II alpha was suggested as the most notable gene involved in the isoproterenol mechanism through inhibitor assays. This study illustrates that isoproterenol significantly enhances endocrine differentiation and underscores its effects on stem cell-derived beta cell maturation, emphasizing its therapeutic potential for the treatment of diabetes.

Comparison of Malondialdehyde, Acetylcholinesterase, and Apoptosis-Related Markers in the Cortex and Hippocampus of Cognitively Dysfunctional Mice Induced by Scopolamine

Objectives: Until now, many researchers have conducted evaluations on hippocampi for analyses of cognitive dysfunction models using scopolamine. However, depending on the purposes of these analyses, there are differences in the experimental results for the hippocampi and cortexes. Therefore, this study intends to compare various analyses of cognitive dysfunction after scopolamine administration with each other in hippocampi and cortexes. Methods: Scopolamine was administered at three dosages in mice: 0.5, 1, and 3 mg/kg. And this study evaluates the differences in cognitive function and the expression of malondialdehyde (MDA), acetylcholinesterase (AChE), and brain-derived neurotrophic factor (BDNF) in mice's hippocampi and cortexes based on scopolamine dosages. Results: The Morris water maze test was conducted between 1 and 3 h after scopolamine injection to assess its duration. A significant decrease in behavioral ability was evaluated at 1 h, and we observed a similar recovery to the normal group at 3 h. And the Morris water maze escape latency showed differences depending on scopolamine concentration. While the escape waiting time in the control group and scop 0.5 administration group remained similar to that seen before administration, the administration of scop 1 and 3 increased it. In the experimental group administered scop 1 and 3, cerebral MDA levels in the cerebral cortex significantly increased. In the hippocampus, the MDA level in the scopolamine-administered groups slightly increased compared to the cortex. A Western blotting assay shows that Bax and Bcl-xl showed a tendency to increase or decrease depending on the concentration, but BDNF increased in scop 0.5, and scop 1 and 3 did not show a significant decrease compared to the control at the cerebral cortex. In the hippocampus, BDNF showed a concentration-dependent decrease in expression. Conclusions: This study's findings indicate that chemical analyses for MDA and AChE can be performed in the cerebral cortex, while the hippocampus is better suited for protein analysis of apoptosis and BDNF.

Discovery of Tetrahydro Tanshinone I as a Naturally Occurring Covalent Pan-Inhibitor Against Gut Microbial Bile Salt Hydrolases

Gut microbial bile salt hydrolases (gmBSHs), an important class of bacteria-produced cysteine hydrolases, play a crucial role in bile acid metabolism. Modulating the total gmBSH activity is a feasible way for ameliorating some metabolic diseases including colorectal cancer, type 2 diabetes, and obesity. This study reported the discovery and characterization of a botanical compound as a covalent pan-inhibitor of gmBSHs. Following the screening of more than 100 botanical compounds, tanshinones were found with strong time-dependent anti-EfBSH effects. After that, a total of 17 naturally occurring tanshinones were collected, and their anti-EfBSH potentials were tested. Among all tested tanshinones, tetrahydro tanshinone I (THTI) exhibited the most potent inhibitory effects against five gmBSHs (EfBSH, LsBSH, BtBSH, CpBSH, and BlBSH), showing the IC50 values ranging from 0.28 ± 0.05 μM to 1.62 ± 0.07 μM. Further investigations showed that THTI could covalently modify the conserved catalytic cysteine (Cys2) of all tested gmBSHs, while this agent could strongly inhibit the total gmBSHs activity in live microorganisms and murine gut luminal content. Collectively, THTI is identified as a naturally occurring covalent pan-inhibitor of gmBSHs, which offers a promising lead compound to develop more efficacious gmBSHs inhibitors for the management of bile acid metabolism and related metabolic disorders.

Identification of novel brain penetrant GSK-3β inhibitors toward Alzheimer's disease therapy by virtual screening, molecular docking, dynamic simulation, and MMPBSA analysis

One of the significant therapeutic targets for Alzheimer's disease (AD) is Glycogen Synthase Kinase-3β (GSK-3β). Inhibition of GSK-3β can prevent hyperphosphorylation of tau, and thus prevent formation and accumulation of neurofibrillary tangles and neuropil threads that block intracellular transport, trigger unfolded protein response, and increase oxidative stress, cumulatively leading to neurodegeneration. In this study, we have performed structure-based virtual screening of two small-molecule libraries from ChemDiv CNS databases using AutoDock Vina to identify hit molecules based on their binding affinities compared to that of an established GSK-3β inhibitor, indirubin-3'-monoxime (IMO). Pharmacoinformatic screening on SwissADME and pkCSM servers enabled identification of lead molecules with favorable pharmacoinformatic properties for drug likeliness, including blood brain barrier (BBB) permeability. Further, molecular dynamic simulations identified six candidate lead molecules that show stable complex formation with GSK-3β in dynamic state under physiological conditions. Principal component analysis of the dynamic state was used to plot Free Energy Landscapes (FELs) of GSK-3β-ligand complexes. STRIDE secondary structure analysis of the lowest energy conformations identified from FEL plots, and binding free energy calculations by Molecular Mechanics Poisson-Boltzmann Surface Area ((ΔGbind)MM-PBSA) of the simulation trajectories led to the identification of two ligands as potential lead molecules having favorable free energy landscape profiles as well as significantly lower (ΔGbind)MM-PBSA in dynamic state compared to that of reference inhibitor IMO. Hence, this study identifies two novel brain penetrant GSK-3β inhibitors that are likely to have therapeutic potential against Alzheimer's disease.

Integrating ADMET, enrichment analysis, and molecular docking approach to elucidate the mechanism of Artemisia herba alba for the treatment of inflammatory bowel disease-associated arthritis

Inflammatory Bowel Disease-Associated Arthritis (IBD-associated arthritis) poses a significant challenge, intertwining the complexities of both inflammatory bowel disease (IBD) and arthritis, significantly compromising patient quality of life. While existing medications offer relief, these drugs often initiate adverse effects, necessitating the requirement for safer therapeutic alternatives. Artemisia herba-alba, a traditional medicinal plant known for its anti-inflammatory properties, emerges as a potential candidate. Our computational study focused on examining 20 bioactive compounds derived from A. herba-alba for potential treatment of IBD-associated arthritis. These compounds detected in A. herba-alba include camphor, alpha-thujone, eucalyptol, cis-chrysanthenyl acetate, vicenin-2, 4,5-di-O-caffeoylquinic acid, chlorogenic acid, hispidulin, isoschaftoside, isovitexin, patuletin-3-glucoside, vanillic acid, rutin, schaftoside, lopinavir, nelfinavir, quercetin, artemisinin, gallic acid, and cinnamic acid. Following rigorous analysis encompassing pharmacokinetics, toxicity profiles, and therapeutic targets, compounds with favorable, beneficial characteristics were identified. In addition, comparative analysis with disease-gene associations demonstrated the interconnectedness of inflammatory pathways across diseases. Molecular docking studies provided mechanistic insights indicating this natural plant components potential to modulate critical inflammatory pathways. Overall, our findings indicate that A. herba-alba-derived compounds may be considered as therapeutic agents for IBD-associated arthritis, warranting further experimental validation and clinical exploration.

Synthesis and evaluation of tetrahydropyrrolo[1,2-a]quinolin-1(2H)-ones as new tubulin polymerization inhibitors

Here we explored new 1,5-disubstituted pyrrolidin-2-ones 1, 2 and 5-aryl-3,3a,4,5-tetrahydropyrrolo[1,2-a]quinoline-1(2H)-ones 3 as inhibitors of tubulin polymerization. We evaluated their effects on microtubule dynamics in vitro and on the proliferation of A549 cells, using flow cytometry-based cell cycle analysis. The results were verified with phase-contrast microscopy in three cancer cell lines: A549, HeLa and MCF-7. Guided by molecular modeling of the interactions between tubulin and the most active of the identified compounds, we designed, synthesized, and tested the 3-hydroxyphenyl-substituted compound 3c. This compound was further shown to bind to the colchicine site of tubulin and reduce microtubule growth rates in vitro. Moreover, compound 3c arrested division of the A549 cells in the low micromolar range (IC50 = 5.9 μM) and exhibited cytotoxicity against four different cell lines in the MTT assay for cell proliferation. Our findings demonstrate that 5-aryltetrahydropyrrolo[1,2-a]quinoline-1(2H)-one is a promising scaffold for the development of novel tubulin polymerization inhibitors.

Alchemical Transformations and Beyond: Recent Advances and Real-World Applications of Free Energy Calculations in Drug Discovery

Computational methods constitute efficient strategies for screening and optimizing potential drug molecules. A critical factor in this process is the binding affinity between candidate molecules and targets, quantified as binding free energy. Among various estimation methods, alchemical transformation methods stand out for their theoretical rigor. Despite challenges in force field accuracy and sampling efficiency, advancements in algorithms, software, and hardware have increased the application of free energy perturbation (FEP) calculations in the pharmaceutical industry. Here, we review the practical applications of FEP in drug discovery projects since 2018, covering both ligand-centric and residue-centric transformations. We show that relative binding free energy calculations have steadily achieved chemical accuracy in real-world applications. In addition, we discuss alternative physics-based simulation methods and the incorporation of deep learning into free energy calculations.

Recent advances from computer-aided drug design to artificial intelligence drug design

Computer-aided drug design (CADD), a cornerstone of modern drug discovery, can predict how a molecular structure relates to its activity and interacts with its target using structure-based and ligand-based methods. Fueled by ever-increasing data availability and continuous model optimization, artificial intelligence drug design (AIDD), as an enhanced iteration of CADD, has thrived in the past decade. AIDD demonstrates unprecedented opportunities in protein folding, property prediction, and molecular generation. It can also facilitate target identification, high-throughput screening (HTS), and synthetic route prediction. With AIDD involved, the process of drug discovery is greatly accelerated. Notably, AIDD offers the potential to explore uncharted territories of chemical space beyond current knowledge. In this perspective, we began by briefly outlining the main workflows and components of CADD. Then through showcasing exemplary cases driven by AIDD in recent years, we describe the evolving role of artificial intelligence (AI) in drug discovery from three distinct stages, that is, chemical library screening, linker generation, and de novo molecular generation. In this process, we attempted to draw comparisons between the features of CADD and AIDD.

Self-organizing maps of unbiased ligand-target binding pathways and kinetics

The interpretation of ligand-target interactions at atomistic resolution is central to most efforts in computational drug discovery and optimization. However, the highly dynamic nature of protein targets, as well as possible induced fit effects, makes difficult to sample many interactions effectively with docking studies or even with large-scale molecular dynamics (MD) simulations. We propose a novel application of Self-Organizing Maps (SOMs) to address the sampling and dynamic mapping tasks, particularly in cases involving ligand flexibility and induced fit. The SOM approach offers a data-driven strategy to create a map of the interaction process and pathways based on unbiased MD. Furthermore, we show how the preliminary SOM mapping is complementary to kinetic analysis, with the employment of both network-based approaches and Markov state models. We demonstrate the method by comprehensively mapping a large dataset of 640 μs of unbiased trajectories sampling the recognition process between the phosphorylated YEEI peptide and its high-specificity target lck-SH2. The integration of SOM into unbiased simulation protocols significantly advances our understanding of the ligand binding mechanism. This approach serves as a potent tool for mapping intricate ligand-target interactions with unprecedented detail, thereby enhancing the characterization of kinetic properties crucial to drug design.

Discovery and mechanistic insights into thieno[3,2-d]pyrimidine and heterocyclic fused pyrimidines inhibitors targeting tubulin for cancer therapy

Guided by the X-ray cocrystal structure of the lead compound 4a, we developed a series of thieno[3,2-d]pyrimidine and heterocyclic fused pyrimidines demonstrating potent antiproliferative activity against four tumor cell lines. Two analogs, 13 and 25d, exhibited IC50 values around 1 nM and overcame P-glycoprotein (P-gp)-mediated multidrug resistance (MDR). At low concentrations, 13 and 25d inhibited both the colony formation of SKOV3 cells in vitro and tubulin polymerization. Furthermore, mechanistic studies showed that 13 and 25d induced G2/M phase arrest and apoptosis in SKOV3 cells, as well as dose-dependent inhibition of tumor cell migration and invasion at low concentrations. Most notably, the X-ray cocrystal structures of compounds 4a, 25a, and the optimal molecule 13 in complex with tubulin were elucidated. This study identifies thieno[3,2-d]pyrimidine and heterocyclic fused pyrimidines as representatives of colchicine-binding site inhibitors (CBSIs) with potent antiproliferative activity.

Exploring the ability of the MD+FoldX method to predict SARS-CoV-2 antibody escape mutations using large-scale data

Antibody escape mutations pose a significant challenge to the effectiveness of vaccines and antibody-based therapies. The ability to predict these escape mutations with computer simulations would allow us to detect threats early and develop effective countermeasures, but a lack of large-scale experimental data has hampered the validation of these calculations. In this study, we evaluate the ability of the MD+FoldX molecular modeling method to predict escape mutations by leveraging a large deep mutational scanning dataset, focusing on the SARS-CoV-2 receptor binding domain. Our results show a positive correlation between predicted and experimental data, indicating that mutations with reduced predicted binding affinity correlate moderately with higher experimental escape fractions. We also demonstrate that higher precision can be achieved using affinity cutoffs tailored to distinct SARS-CoV-2 antibodies from four different classes rather than a one-size-fits-all approach. Further, we suggest that the quartile values of optimized cutoffs reported for each class in this study can serve as a valuable guide for future work on escape mutation predictions. We find that 70% of the systems surpass the 50% precision mark, and demonstrate success in identifying mutations present in significant variants of concern and variants of interest. Despite promising results for some systems, our study highlights the challenges in comparing predicted and experimental values. It also emphasizes the need for new binding affinity methods with improved accuracy that are fast enough to estimate hundreds to thousands of antibody-antigen binding affinities.