Changing Paradigm from one Target one Ligand Towards Multi-target Directed Ligand Design for Key Drug Targets of Alzheimer Disease: An Important Role of In Silico Methods in Multi-target Directed Ligands Design

Carvacrol/thymol derivatives as highly selective BuChE inhibitors with anti-inflammatory activities: Discovery and bio-evaluation

In this study, nine novel carvacrol/thymol derivatives incorporating carbamate groups were designed, synthesized, and evaluated as multifunctional anti-AD agents. These derivatives displayed superior BuChE inhibitory and anti-inflammatory characteristics compared to the parent compounds. While the derivatives exhibited AChE IC50 values exceeding the detectable limit (>100 μM), they demonstrated high potency as BuChE inhibitors, with IC50 values ranging from 0.05 to 9.62 μM. In an inflammation model of BV2 microglial cells induced by lipopolysaccharide (LPS), the derivatives effectively reduced the levels of the pro-inflammatory cytokine interleukin-1β (IL1β), with inhibition rates of IL1β exceeding 50 % at 10 μM. Notably, compound SXF3 ‌attained the highest BuChE inhibition efficacy (eqBuChE IC50 = 0.05 ± 0.003 μM, hBuChE IC50 = 0.04 ± 0.001 μM), the highest selectivity for BuChE (with a selectivity index, SI, exceeding 2000, calculated as the ratio of eeAChE IC50 to eqBuChE IC50) and high anti-inflammatory activity (inhibition of IL1β, IC50 = 8.33 ± 0.08 μM). In a scopolamine-induced AD mouse model, SXF3 (15 mg/kg) significantly reduced the latency to the platform and attenuated memory deficits. Biochemical analysis confirmed that SXF3 significantly increased acetylcholine (ACh) levels in the mice hippocampus, primarily due to the inhibition of BuChE rather than AChE, and that SXF3 significantly reduced IL1β levels to normal, further confirming its anti-inflammatory activities. Hence, the selective BuChE inhibitory properties and anti-inflammatory attributes of SXF3 render it a promising candidate for further investigation in the treatment of AD.

Queuine as a potential multi-target drug for alzheimer's disease: insights from protein dynamics

Alzheimer's disease (AD) is a neurodegenerative disorder with a complex pathogenesis. One promising approach to treating AD is simultaneously targeting multiple aspects of the disease using a multi-target drug (MTD). In this study, multi-target drug (MTD) potential of the nutraceutical molecule Queuine was explored using molecular docking and molecular dynamics (MD) simulations with five different protein targets engaged in AD: AChE, beta-site amyloid precursor protein cleaving enzyme-1 (BACE-1), N-methyl-D-aspartate receptor (NMDAR), monoamine oxidase A (MAO-A), and Synapsin III. Queuine revealed significant binding affinities, the docking scores being -10.1, -5.97, -5.63, -8.40, and -10.56 kcal/mol for AChE, BACE-1, NMDAR, MAO-A, and Synapsin III, respectively. MD simulations showed that Queuine formed stable complexes and preserved its stability throughout the simulation, the backbone fluctuations remaining within 2.5 Å specifically in the case of the BACE-1. Elastic network model simulations and principal component analysis were carried out to illustrate the dynamics of the protein systems. Significant hinge-bending and twisting-type motions that may be relevant to function were observed around the dimerization interfaces or binding sites. Structural clustering based on PCA analysis and cross-correlation maps demonstrated that Queuine binding altered the protein dynamics more drastically in the case of highly mobile proteins NMDAR and MAO-A. We propose that the neuroprotective effect of Queuine may stem from its prominent inhibitory action on enzymes BACE-1 and AChE. Our results suggest that Queuine may serve as a promising MTD candidate for the treatment of AD.Communicated by Ramaswamy H. Sarma.

AlzyFinder: A Machine-Learning-Driven Platform for Ligand-Based Virtual Screening and Network Pharmacology

Alzheimer's disease (AD), a prevalent neurodegenerative disorder, presents significant challenges in drug development due to its multifactorial nature and complex pathophysiology. The AlzyFinder Platform, introduced in this study, addresses these challenges by providing a comprehensive, free web-based tool for parallel ligand-based virtual screening and network pharmacology, specifically targeting over 85 key proteins implicated in AD. This innovative approach is designed to enhance the identification and analysis of potential multitarget ligands, thereby accelerating the development of effective therapeutic strategies against AD. AlzyFinder Platform incorporates machine learning models to facilitate the ligand-based virtual screening process. These models, built with the XGBoost algorithm and optimized through Optuna, were meticulously trained and validated using robust methodologies to ensure high predictive accuracy. Validation included extensive testing with active, inactive, and decoy molecules, demonstrating the platform's efficacy in distinguishing active compounds. The models are evaluated based on balanced accuracy, precision, and F1 score metrics. A unique soft-voting ensemble approach is utilized to refine the classification process, integrating the strengths of individual models. This methodological framework enables a comprehensive analysis of interaction data, which is presented in multiple formats such as tables, heat maps, and interactive Ligand-Protein Interaction networks, thus enhancing the visualization and analysis of drug-protein interactions. AlzyFinder was applied to screen five molecules recently reported (and not used to train or validate the ML models) as active compounds against five key AD targets. The platform demonstrated its efficacy by accurately predicting all five molecules as true positives with a probability greater than 0.70. This result underscores the platform's capability in identifying potential therapeutic compounds with high precision. In conclusion, AlzyFinder's innovative approach extends beyond traditional virtual screening by incorporating network pharmacology analysis, thus providing insights into the systemic actions of drug candidates. This feature allows for the exploration of ligand-protein and protein-protein interactions and their extensions, offering a comprehensive view of potential therapeutic impacts. As the first open-access platform of its kind, AlzyFinder stands as a valuable resource for the AD research community, available at http://www.alzyfinder-platform.udec.cl with supporting data and scripts accessible via GitHub https://github.com/ramirezlab/AlzyFinder.

Deciphering the multi-functional role of Indian propolis for the management of Alzheimer's disease by integrating LC-MS/MS, network pharmacology, molecular docking, and in-vitro studies

The conventional one-drug-one-disease theory has lost its sheen in multigenic diseases such as Alzheimer's disease (AD). Propolis, a honeybee-derived product has ethnopharmacological evidence of antioxidant, anti-inflammatory, antimicrobial and neuroprotective properties. However, the chemical composition is complex and highly variable geographically. So, to leverage the potential of propolis as an effective treatment modality, it is essential to understand the role of each phytochemical in the AD pathophysiology. Therefore, the present study was aimed at investigating the anti-Alzheimer effect of bioactive in Indian propolis (IP) by combining LC-MS/MS fingerprinting, with network-based analysis and experimental validation. First, phytoconstituents in IP extract were identified using an in-house LC-MS/MS method. The drug likeness and toxicity were assessed, followed by identification of AD targets. The constituent-target-gene network was then constructed along with protein-protein interactions, gene pathway, ontology, and enrichment analysis. LC-MS/MS analysis identified 16 known metabolites with druggable properties except for luteolin-5-methyl ether. The network pharmacology-based analysis revealed that the hit propolis constituents were majorly flavonoids, whereas the main AD-associated targets were MAOB, ESR1, BACE1, AChE, CDK5, GSK3β, and PTGS2. A total of 18 gene pathways were identified to be associated, with the pathways related to AD among the topmost enriched. Molecular docking analysis against top AD targets resulted in suitable binding interactions at the active site of target proteins. Further, the protective role of IP in AD was confirmed with cell-line studies on PC-12, in situ AChE inhibition, and antioxidant assays.

Screening Marine Microbial Metabolites as Promising Inhibitors of Borrelia garinii: A Structural Docking Approach towards Developing Novel Lyme Disease Treatment

Lyme disease caused by the Borrelia species is a growing health concern in many parts of the world. Current treatments for the disease may have side effects, and there is also a need for new therapies that can selectively target the bacteria. Pathogens responsible for Lyme disease include B. burgdorferi, B. afzelii, and B. garinii. In this study, we employed structural docking-based screening to identify potential lead-like inhibitors against the bacterium. We first identified the core essential genome fraction of the bacterium, using 37 strains. Later, we screened a library of lead-like marine microbial metabolites (n = 4730) against the arginine deiminase (ADI) protein of Borrelia garinii. This protein plays a crucial role in the survival of the bacteria, and inhibiting it can kill the bacterium. The prioritized lead compounds demonstrating favorable binding energies and interactions with the active site of ADI were then evaluated for their drug-like and pharmacokinetic parameters to assess their suitability for development as drugs. Results from molecular dynamics simulation (100 ns) and other scoring parameters suggest that the compound CMNPD18759 (common name: aureobasidin; IUPAC name: 2-[(4R,6R)-4,6-dihydroxydecanoyl]oxypropan-2-yl (3S,5R)-3,5-dihydroxydecanoate) holds promise as a potential drug candidate for the treatment of Lyme disease, caused by B. garinii. However, further experimental studies are needed to validate the efficacy and safety of this compound in vivo.

Potentiality of bioactive compounds as inhibitor of M protein and F protein function of human respiratory syncytial virus

The human respiratory syncytial virus (RSV) creates a pandemic every year in several countries in the world. Lack of target therapeutics and absence of vaccines have prompted scientists to create novel vaccines or small chemical treatments against RSV's numerous targets. The matrix (M) protein and fusion (F) glycoprotein of RSV are well characterized and attractive drug targets. Five bioactive compounds from Alnus japonica (Thunb.) Steud. were taken into consideration as lead compounds. Drug-likeness characters of them showed the drugs are non-toxic and non-mutagenic and mostly lipophobic. Molecular docking reveals that all bioactive compounds have better binding and better inhibitory effect than ribavirin which is currently used against RSV. Praecoxin A appeared as the best lead compound between them. It creates 7 different types of bonds with amino acids of M protein and 5 different types of bonds with amino acids of F protein. Van der Waals interactions highly influenced the binding energies. Molecular dynamic simulations represent the non-deviated and less fluctuating nature of praecoxin A. Principal Component Analysis showed praecoxin A complex with RSV matrix protein is more stable than ribavirin complex. This study will help to develop a new drug to inhibit RSV. All ligands were minimized through semi-empirical PM3 process with MOPAC. Toxicity was tested by ProTox-II server. Molecular docking studies were carried out using AutoDock 4.2. Molecular dynamics simulations for 100 ns were carried out through GROMACS 5.12 MD and GROMOS96 43a1 force field. The graphs were produced by GROMACS's XMGrace program.

Graphical abstract

Multitarget antibacterial drugs: An effective strategy to combat bacterial resistance

The rise of antibiotic resistance and the decrease in the discovery of new antibiotics have caused a global health crisis. Of particular concern is the fact that despite efforts to develop new antibiotics, drug discovery is unable to keep up with the rapid development of resistance. This ongoing crisis highlights the fact that single-target drugs may not always exhibit satisfactory therapeutic effects and are prone to target mutations and resistance due to the complexity of bacterial mechanisms. Retrospective studies have shown that most successful antibiotics have multiple targets. Compared with single-target drugs, successfully designed multitarget drugs can simultaneously regulate multiple targets to reduce resistance caused by single-target mutations or expression changes. In addition to a lower risk of drug-drug interactions, multitarget drugs show superior pharmacokinetics and higher patient compliance compared with combination therapies. Therefore, to reduce resistance, many efforts have been made to discover and design multitarget drugs with different chemical structures and functions. Although there have been numerous studies on how to develop drugs and slow down the development of drug resistance, the reduction of bacterial resistance by multitarget antibacterial drugs has not received widespread attention and is rarely mentioned in the peer-reviewed literature. This review summarises the development of antibiotic resistance and the mechanisms proposed for its emergence, examines the potential of multitarget drugs as an effective strategy to slow the development of resistance, and discusses the rationale for multitarget drug therapy. We also describe multitarget antibacterial compounds with the potential to reduce drug resistance and the available strategies to develop multitarget drugs.

Threat of respiratory syncytial virus infection knocking the door: a proposed potential drug candidate through molecular dynamics simulations, a future alternative

The discovery of antiviral approaches to prevent or cure respiratory syncytial virus (RSV) infections is critical, particularly because RSV is one of the most common causes of infant respiratory problems. There is currently no approved vaccination available to treat RSV infections. FDA has approved the drug ribavirin, but it is not sufficient to treat RSV. This work aimed to find and study in silico anti-RSV drugs that target matrix protein and nucleoprotein. In this study, we have identified five drug candidates that had better binding energies than ribavirin. Garenoxacin appeared as top lead compounds between them. AutoDock Vina was used to execute molecular docking of a library of chosen chemicals. The high-score compound was then confirmed using the Maestro 12.3 module's molecular dynamics simulation and the binding energies derived using Prime/Molecular Mechanics Generalized Born Surface Area (Prime/MM-GBSA). Comparative molecular dynamics simulations revealed that garenoxacin has better stability and high residue contacts with high binding affinity than ribavirin. This study showed garenoxacin could prevent RSV infection better than ribavirin. In pursuing a more effective RSV control drug, additional research into these chemicals in vitro and in vivo is essential.

Integrative applications of network pharmacology and molecular docking: An herbal formula ameliorates H9c2 cells injury through pyroptosis

Background

QiShen YiQi pills (QSYQ) is a Traditional Chinese Medicine (TCM) formula, which has a significant effect on the treatment of patients with myocardial infarction (MI) in clinical practice. However, the molecular mechanism of QSYQ regulation pyroptosis after MI is still not fully known. Hence, this study was designed to reveal the mechanism of the active ingredient in QSYQ.

Methods

Integrated approach of network pharmacology and molecular docking, were conducted to screen active components and corresponding common target genes of QSYQ in intervening pyroptosis after MI. Subsequently, STRING and Cytoscape were applied to construct a PPI network, and obtain candidate active compounds. Molecular docking was performed to verify the binding ability of candidate components to pyroptosis proteins and oxygen-glucose deprivation (OGD) induced cardiomyocytes injuries were applied to explore the protective effect and mechanism of the candidate drug.

Results

Two drug-likeness compounds were preliminarily selected, and the binding capacity between Ginsenoside Rh2 (Rh2) and key target High Mobility Group Box 1 (HMGB1)was validated in the form of hydrogen bonding. 2 μM Rh2 prevented OGD-induced H9c2 death and reduced IL-18 and IL-1β levels, possibly by decreasing the activation of the NLRP3 inflammasome, inhibiting the expression of p12-caspase1, and attenuating the level of pyroptosis executive protein GSDMD-N.

Conclusions

We propose that Rh2 of QSYQ can protect myocardial cells partially by ameliorating pyroptosis, which seems to have a new insight regarding the therapeutic potential for MI.

The importance of selecting crystal form for triazole fungicide tebuconazole to enhance its botryticidal activity

The growing evidences of resistant fungi stimulate fully understanding tebuconazole regarding its crystal structure on fungicidal activity. In this study, the crystal structures of six technical tebuconazoles (BX, HH, JP, QZ, SJ, and YT) were characterized by using high-resolution X-ray powder diffraction and three-dimensional crystal structure modeling. A structure-activity relationship of the tebuconazoles on the susceptible (HLS and YJS) or resistant (XHR) Botrytis cinerea isolates was analyzed, the differential tricarboxylic acid (TCA) cycle metabolism was determined, and molecular docking with sterol 14α-demethylase (CYP51) was performed. The results showed that tebuconazole existed in three types of crystal forms: an overlapping-pair conformation, a side-by-side-pair conformation, and a parallel-pair conformation. QZ with the parallel-pair conformation and the minimum crystal cell volume exhibited a higher activity and a lower resistant level. XHR possessed a higher content of TCA cycle metabolites and phosphate than YJS, but the exposure to QZ significantly reduced the contents of citrate, isocitrate, α-ketoglutarate and oxaloacetate in XHR, as did the exposure to other technical tebuconazoles. Moreover, the point mutations F487L, G464S, and G443S altered the binding properties of chiral stereoscopic R-QZ with CYP51 protein. Especially the G443S mutation promoted a weak linking of R-QZ with LEU380 and TYR126, and greatly slashed the binding action at lower docking score. In conclusion, our results evidenced an efficient crystal conformation of tebuconazole to improve botryticidal activity and a potential adaptability of B. cinerea to tebuconazole inhibition in TCA cycle metabolism and CYP51 protein mutation.

CADMA-Chem: A Computational Protocol Based on Chemical Properties Aimed to Design Multifunctional Antioxidants

A computational protocol aimed to design new antioxidants with versatile behavior is presented. It is called Computer-Assisted Design of Multifunctional Antioxidants and is based on chemical properties (CADMA-Chem). The desired multi-functionality consists of in different methods of antioxidant protection combined with neuroprotection, although the protocol can also be used to pursue other health benefits. The dM38 melatonin derivative is used as a study case to illustrate the protocol in detail. This was found to be a highly promising candidate for the treatment of neurodegeneration, in particular Parkinson's and Alzheimer's diseases. This also has the desired properties of an oral-drug, which is significantly better than Trolox for scavenging free radicals, and has chelates redox metals, prevents the ●OH production, via Fenton-like reactions, repairs oxidative damage in biomolecules (lipids, proteins, and DNA), and acts as a polygenic neuroprotector by inhibiting catechol-O-methyl transferase (COMT), acetylcholinesterase (AChE) and monoamine oxidase B (MAOB). To the best of our best knowledge, CADMA-Chem is currently the only protocol that simultaneously involves the analyses of drug-like behavior, toxicity, manufacturability, versatile antioxidant protection, and receptor-ligand binding affinities. It is expected to provide a starting point that helps to accelerate the discovery of oral drugs with the potential to prevent, or slow down, multifactorial human health disorders.

Sauropus brevipes ethanol extract negatively regulates inflammatory responses in vivo and in vitro by targeting Src, Syk and IRAK1

CONTEXT

Sauropus brevipes Müll. Arg. (Phyllanthaceae) has been used as an effective ingredient in a decoction for the treatment of diarrhoea. However, there was no report on its modulatory role in inflammation.

OBJECTIVE

This study investigates anti-inflammatory effect of S. brevipes in various inflammation models.

MATERIALS AND METHODS

The aerial part of S. brevipes was extracted with 95% ethanol to produce Sb-EE. RAW264.7 cells pre-treated with Sb-EE were stimulated by lipopolysaccharide (LPS), and Griess assay and PCR were performed. High-performance liquid chromatography (HPLC) analysis, luciferase assay, Western blotting and kinase assay were employed. C57BL/6 mice (10 mice/group) were orally administered with Sb-EE (200 mg/kg) once a day for five days, and peritonitis was induced by an intraperitoneal injection of LPS (10 mg/kg). ICR mice (four mice/group) were orally administered with Sb-EE (20 or 200 mg/kg) or ranitidine (positive control) twice a day for two days, and EtOH/HCl was orally injected to induce gastritis.

RESULTS

Sb-EE suppressed nitric oxide (NO) release (IC₅₀=34 µg/mL) without cytotoxicity and contained flavonoids (quercetin, luteolin and kaempferol). Sb-EE (200 µg/mL) reduced the mRNA expression of inducible NO synthase (iNOS). Sb-EE blocked the activities of Syk and Src, while inhibiting interleukin-1 receptor associated kinases (IRAK1) by 68%. Similarly, orally administered Sb-EE (200 mg/kg) suppressed NO production by 78% and phosphorylation of Src and Syk in peritonitis mice. Sb-EE also decreased inflammatory lesions in gastritis mice.

DISCUSSION AND CONCLUSIONS

This study demonstrates the inhibitory effect of Sb-EE on the inflammatory response, suggesting that Sb-EE can be developed as a potential anti-inflammatory agent.

Nutraceuticals in mental diseases - Bridging the gap between traditional use and modern pharmacology

In evidence-based pharmacotherapy, the complexity of etiopathogenesis and pathophysiology of mental diseases has attracted comparably little consideration so far. The choice of currently available pharmacotherapies is predominantly guided by specific clinical phenotypes and is limited by low response rates and clinically relevant side effects. Nutraceuticals typically represent multicomponent compounds and may offer high therapeutic potential, by simultaneously addressing multiple aspects in mental disease pathogenesis with rather little side effects. Here, recent pharmacological research on natural products is assessed with focus on a multitarget therapeutic concept, based on shared molecular mechanisms, and in particular, on how far nutraceuticals might address such multitargets. Overcoming deficits regarding clearly defined compositions, concentration-dependent and causative structure-activity-response relationships, evaluation of bioavailability, metabolic fate, and long-term safety are crucial for translating potential plant-based drug candidates into proof-of-concept clinical studies.

Identification of phytochemicals from North African plants for treating Alzheimer's diseases and of their molecular targets by in silico network pharmacology approach

BACKGROUND

The global social expenses of Alzheimer's disease (AD) have been increased to US$1 trillion due to high cost, side-effects, and low efficiency of the current AD-therapies. Another reason is the lack of preventive drugs and the low-income situation of Asian and African countries. Accordingly, patients rather prefer traditional herbal remedies. Network-pharmacology has been a well-established method for the visualization and the construction of disorder target protein-drug framework. This could aid in the identification of drugs molecular-mechanisms.

AIM

The aim of this study is to investigate the phytochemical constituents that could target Alzheimer's disease from the North African plants. This could be done by exploring their possible mechanisms of action through molecular network pharmacology-based approach.

EXPERIMENTAL PROCEDURE

The Phytochemical-compounds of North-African plants (NAP) have been accessed from open-databank. ADME-screening has been conducted for filtering of the NAP phytochemical-constituents utilizing Qikprop-software. The open STITCH databank has been utilized for the prediction of the phytochemical-constituents target-proteins; UniProt and TDD-DB databanks have been utilized for distinguishing AD-related proteins. Phytochemical constituent-target protein (C-T) and plant-phytochemical constituent-target protein (P-C-T) frameworks have been assembled utilizing Cytoscape to interpret the anti-Alzheimer's disease mechanism of action of the targeted phytochemical constituents.

RESULTS

The NAP 6842 phytochemical-constituents (from more than 1000 plants) have been exposed to ADME and CNS modulating filtration, generating 94 phytochemical-constituents which have been subjected to target-prediction investigation. The 94 phytochemical-constituents and the 4 AD-identified targets have been associated through 155 edges which formed the main pathways related to AD. Cuparene, alpha-selinene, beta-sesquiphellandrene, calamenene, 2-4-dimethylheptane, undecane, n-tetradecane, hexadecane, nonadecane, n-eicosane, and heneicosane have had C-T network highest combined-score, whilst the proteins MAO-B, HMG-CoA, BACE1, and GCR have been the most enriched ones by comprising the uppermost combined-scores of C-T. Hypericum perforatum, Piper nigrum, Juniperus communis, Levisticum officinale, Origanum vulgare acquired the uppermost number of P-C-Target interactions.

CONCLUSION

The phytochemical-targets prediction of NAP utilizing molecular-network pharmacology-based investigation has paved the way for networking multi-target, multi-constituent, and multi-pathway mechanisms. This may introduce potential future targets for the regulation and the management of Alzheimer's disease.

TAXONOMY CLASSIFICATION BY EVISE

Alzheimer's disease, Network pharmacology, In-silico computer based approach.

A Comprehensive Review of Cholinesterase Modeling and Simulation

The present article reviews published efforts to study acetylcholinesterase and butyrylcholinesterase structure and function using computer-based modeling and simulation techniques. Structures and models of both enzymes from various organisms, including rays, mice, and humans, are discussed to highlight key structural similarities in the active site gorges of the two enzymes, such as flexibility, binding site location, and function, as well as differences, such as gorge volume and binding site residue composition. Catalytic studies are also described, with an emphasis on the mechanism of acetylcholine hydrolysis by each enzyme and novel mutants that increase catalytic efficiency. The inhibitory activities of myriad compounds have been computationally assessed, primarily through Monte Carlo-based docking calculations and molecular dynamics simulations. Pharmaceutical compounds examined herein include FDA-approved therapeutics and their derivatives, as well as several other prescription drug derivatives. Cholinesterase interactions with both narcotics and organophosphate compounds are discussed, with the latter focusing primarily on molecular recognition studies of potential therapeutic value and on improving our understanding of the reactivation of cholinesterases that are bound to toxins. This review also explores the inhibitory properties of several other organic and biological moieties, as well as advancements in virtual screening methodologies with respect to these enzymes.

Mapping drug-target interactions and synergy in multi-molecular therapeutics for pressure-overload cardiac hypertrophy

Advancements in systems biology have resulted in the development of network pharmacology, leading to a paradigm shift from "one-target, one-drug" to "target-network, multi-component therapeutics". We employ a chimeric approach involving in-vivo assays, gene expression analysis, cheminformatics, and network biology to deduce the regulatory actions of a multi-constituent Ayurvedic concoction, Amalaki Rasayana (AR) in animal models for its effect in pressure-overload cardiac hypertrophy. The proteomics analysis of in-vivo assays for Aorta Constricted and Biologically Aged rat models identify proteins expressed under each condition. Network analysis mapping protein-protein interactions and synergistic actions of AR using multi-component networks reveal drug targets such as ACADM, COX4I1, COX6B1, HBB, MYH14, and SLC25A4, as potential pharmacological co-targets for cardiac hypertrophy. Further, five out of eighteen AR constituents potentially target these proteins. We propose a distinct prospective strategy for the discovery of network pharmacological therapies and repositioning of existing drug molecules for treating pressure-overload cardiac hypertrophy.

From Hybrids to New Scaffolds: The Latest Medicinal Chemistry Goals in Multi-target Directed Ligands for Alzheimer's Disease

Alzheimer's disease (AD) is a chronic, progressive, and fatal neurodegenerative disorder affecting cognition, behavior, and function, being one of the most common causes of mental deterioration in elderly people. Once thought as being just developed because of β amyloid depositions or neurofibrillary Tau tangles, during the last decades, numerous AD-related targets have been established, the multifactorial nature of AD became evident. In this context, the one drug-one target paradigm has resulted in being inefficient in facing AD and other disorders with complex etiology, opening the field for the emergence of the multitarget approach. In this review, we highlight the recent advances within this area, emphasizing in hybridization tools of well-known chemical scaffolds endowed with pharmacological properties concerning AD, such as curcumin-, resveratrol-, chromone- and indole-. We focus mainly on well established and incipient AD therapeutic targets, AChE, BuChE, MAOs, β-amyloid deposition, 5-HT4 and Serotonin transporter, with the aim to shed light about new insights in the AD multitarget therapy.

A comprehensive application: Molecular docking and network pharmacology for the prediction of bioactive constituents and elucidation of mechanisms of action in component-based Chinese medicine

Traditional Chinese medicine (TCM) has been used for more than 2000 years in China. TCM has received wide attention recently due to its unique charm. At the same time, its main obstacles have attracted wide attention, including vagueness of drug composition and treatment mechanism. With the development of virtual screening technology, more and more Chinese medicine compounds have been studied to discover the potential active components and mechanisms of action. Molecular docking is a computer technology based on structural design. Network pharmacology establishes powerful and comprehensive databases to understand the relationship between TCM and disease network. In this review, emergent uses and applications of two techniques and further superiorities of the two techniques when embarked to boil down into a tidy system were illustrated. A combination of the two provides a theoretical basis and technical support for the construction of modern TCM based on the compatibility of components and accelerates the realization of two basic elements as well, including the clearness of the pharmacodynamic substances and explanation of the effect of TCM.

Network-based approach highlighting interplay among anti-hypertensives: target coding-genes: diseases

Elucidating the relation between the medicines: targets, targets: diseases and diseases: diseases are of fundamental significance as-is for societal benefit. Hypertension is one of the dangerous health conditions prevalent in society, is a risk factor for several other diseases if left untreated and anti-hypertensives (AHs) are the approved drugs to treat it. The goal of the study is to decipher the connection between hypertension with other health conditions, however, is challenging due to the large interactome. To fulfill the aim, the strategy involves prior clustering of the AHs into groups as per our previous method, followed by the analyzing functional association of the target coding-genes (tc-genes) and health conditions for each group. Following our recently published work where the AHs are clustered into six groups such that molecules having similar patterns come together, here, the distribution of molecular functions and the cellular components adopted by the tc-genes of each group are analyzed. The analyses indicate that kidney, heart, brain or lung related ailments are commonly associated with the tc-genes. The association of selective tc-genes to health conditions suggests a preference for certain health conditions despite many possibilities. Analyses of experimentally validated drug–drug combinations indicate the trend in successful AHs combinations. Clinically validated combinations bind different targets. Our study provides a promising methodology in a network-based approach that considers the influence of structural diversity of AHs to the functional perspective of tc-genes concerning the health conditions. The method could be extended to explore disease–disease relationships.

Tick Salivary Compounds for Targeted Immunomodulatory Therapy

Immunodeficiency disorders and autoimmune diseases are common, but a lack of effective targeted drugs and the side-effects of existing drugs have stimulated interest in finding therapeutic alternatives. Naturally derived substances are a recognized source of novel drugs, and tick saliva is increasingly recognized as a rich source of bioactive molecules with specific functions. Ticks use their saliva to overcome the innate and adaptive host immune systems. Their saliva is a rich cocktail of molecules including proteins, peptides, lipid derivatives, and recently discovered non-coding RNAs that inhibit or modulate vertebrate immune reactions. A number of tick saliva and/or salivary gland molecules have been characterized and shown to be promising candidates for drug development for vertebrate immune diseases. However, further validation of these molecules at the molecular, cellular, and organism levels is now required to progress lead candidates to clinical testing. In this paper, we review the data on the immuno-pharmacological aspects of tick salivary compounds characterized in vitro and/or in vivo and present recent findings on non-coding RNAs that might be exploitable as immunomodulatory therapies.

Stem cell therapy for Alzheimer's disease

Alzheimer's disease (AD) is a progressive neurodegenerative disease characterized by memory loss and cognitive impairment. It is caused by synaptic failure and excessive accumulation of misfolded proteins. To date, almost all advanced clinical trials on specific AD-related pathways have failed mostly due to a large number of neurons lost in the brain of patients with AD. Also, currently available drug candidates intervene too late. Stem cells have improved characteristics of self-renewal, proliferation, differentiation, and recombination with the advent of stem cell technology and the transformation of these cells into different types of central nervous system neurons and glial cells. Stem cell treatment has been successful in AD animal models. Recent preclinical studies on stem cell therapy for AD have proved to be promising. Cell replacement therapies, such as human embryonic stem cells or induced pluripotent stem cell-derived neural cells, have the potential to treat patients with AD, and human clinical trials are ongoing in this regard. However, many steps still need to be taken before stem cell therapy becomes a clinically feasible treatment for human AD and related diseases. This paper reviews the pathophysiology of AD and the application prospects of related stem cells based on cell type.

Antioxidant Potential of Psychotropic Drugs: From Clinical Evidence to In Vitro and In Vivo Assessment and toward a New Challenge for in Silico Molecular Design

Due to high oxygen consumption, the brain is particularly vulnerable to oxidative stress, which is considered an important element in the etiopathogenesis of several mental disorders, including schizophrenia, depression and dependencies. Despite the fact that it is not established yet whether oxidative stress is a cause or a consequence of clinic manifestations, the intake of antioxidant supplements in combination with the psychotropic therapy constitutes a valuable solution in patients' treatment. Anyway, some drugs possess antioxidant capacity themselves and this aspect is discussed in this review, focusing on antipsychotics and antidepressants. In the context of a collection of clinical observations, in vitro and in vivo results are critically reported, often highlighting controversial aspects. Finally, a new challenge is discussed, i.e., the possibility of assessing in silico the antioxidant potential of these drugs, exploiting computational chemistry methodologies and machine learning. Despite the physiological environment being incredibly complex and the detection of meaningful oxidative stress biomarkers being all but an easy task, a rigorous and systematic analysis of the structural and reactivity properties of antioxidant drugs seems to be a promising route to better interpret therapeutic outcomes and provide elements for the rational design of novel drugs.

Rational design of affinity ligands for bioseparation

Affinity adsorbents have been the cornerstone in protein purification. The selective nature of the molecular recognition interactions established between an affinity ligands and its target provide the basis for efficient capture and isolation of proteins. The plethora of affinity adsorbents available in the market reflects the importance of affinity chromatography in the bioseparation industry. Ligand discovery relies on the implementation of rational design techniques, which provides the foundation for the engineering of novel affinity ligands. The main goal for the design of affinity ligands is to discover or improve functionality, such as increased stability or selectivity. However, the methodologies must adapt to the current needs, namely to the number and diversity of biologicals being developed, and the availability of new tools for big data analysis and artificial intelligence. In this review, we offer an overview on the development of affinity ligands for bioseparation, including the evolution of rational design techniques, dating back to the years of early discovery up to the current and future trends in the field.

Alzheimer's Disease Pharmacotherapy in Relation to Cholinergic System Involvement

Alzheimer’s disease, a major and increasing global health challenge, is an irreversible, progressive form of dementia, associated with an ongoing decline of brain functioning. The etiology of this disease is not completely understood, and no safe and effective anti-Alzheimer’s disease drug to prevent, stop, or reverse its evolution is currently available. Current pharmacotherapy concentrated on drugs that aimed to improve the cerebral acetylcholine levels by facilitating cholinergic neurotransmission through inhibiting cholinesterase. These compounds, recognized as cholinesterase inhibitors, offer a viable target across key sign domains of Alzheimer’s disease, but have a modest influence on improving the progression of this condition. In this paper, we sought to highlight the current understanding of the cholinergic system involvement in Alzheimer’s disease progression in relation to the recent status of the available cholinesterase inhibitors as effective therapeutics.

Dreaming of a New World Where Alzheimer's Is a Treatable Disorder

Alzheimer’s disease (AD) is the most common form of dementia. It’s a chronic and untreatable neurodegenerative disease with irreversible progression and has important social and economic implications in terms of direct medical and social care costs. Despite prolonged and expensive efforts employed by the scientific community over the last few decades, no effective treatments are still available for patients, and the development of disease-modifying drugs is now a really urgent need. The recent failure of clinical trials based on the immunotherapeutic approach against amyloid-β(Aβ) protein questioned the validity of the “amyloid cascade hypothesis” as the molecular machinery causing the disease. Indeed, most attempts to design effective treatments for AD have been based until now on molecular targets suggested to be implicated in AD pathogenesis by the amyloid cascade hypothesis. However, mounting evidence from scientific literature supports the view of AD as a multifactorial disease that results from the concomitant action of multiple molecular players. This view, together with the lack of success of the disease-modifying single-target approaches, strongly suggests that AD drug design needs to be shifted towards multi-targeted compounds or drug combinations acting synergistically on the main core features of disease pathogenesis. The discovery of drug candidates targeting multiple factors involved in AD would greatly improve drug development. So, it is reasonable that upcoming strategies for the design of preventive and/or therapeutic agents for AD point to a multi-pronged approach including more than one druggable target to definitely defeat the disease.

Search for new multi-target compounds against Alzheimer's disease among histamine H3 receptor ligands

Multi-target-directed ligands seem to be an interesting approach to the treatment of complex disorders such as Alzheimer's disease. The aim of the present study was to find novel multifunctional compounds in a non-imidazole histamine H₃ receptor ligand library. Docking-based virtual screening was applied for selection of twenty-six hits which were subsequently evaluated in Ellman's assay for the inhibitory potency toward acetyl- (AChE) and butyrylcholinesterase (BuChE). The virtual screening with high success ratio enabled to choose multi-target-directed ligands. Based on docking results, all selected ligands were able to bind both catalytic and peripheral sites of AChE and BuChE. The most promising derivatives combined the flavone moiety via a six carbon atom linker with a heterocyclic moiety, such as azepane, piperidine or 3-methylpiperidine. They showed the highest inhibitory activities toward cholinesterases as well as well-balanced potencies against H₃R and both enzymes. Two derivatives were chosen - 5 (IC₅₀ = 0.46 μM (AChE); 0.44 μM (BuChE); K_i = 159.8 nM (H₃R)) and 17 (IC₅₀ = 0.50 μM (AChE); 0.76 μM (BuChE); K_i = 228.2 nM (H₃R)), and their inhibition mechanism was evaluated in kinetic studies. Both compounds displayed non-competitive mode of AChE and BuChE inhibition. Compounds 5 and 17 might serve as good lead structures for further optimization and development of novel multi-target anti-Alzheimer's agents.

Jowiseungchungtang Inhibits Amyloid-β Aggregation and Amyloid-β-Mediated Pathology in 5XFAD Mice

Alzheimer's disease (AD) is a neurodegenerative disease, which is accompanied by memory loss and cognitive dysfunction. Although a number of trials to treat AD are in progress, there are no drugs available that inhibit the progression of AD. As the aggregation of amyloid-β (Aβ) peptides in the brain is considered to be the major pathology of AD, inhibition of Aβ aggregation could be an effective strategy for AD treatment. Jowiseungchungtang (JWS) is a traditional oriental herbal formulation that has been shown to improve cognitive function in patients or animal models with dementia. However, there are no reports examining the effects of JWS on Aβ aggregation. Thus, we investigated whether JWS could protect against both Aβ aggregates and Aβ-mediated pathology such as neuroinflammation, neurodegeneration, and impaired adult neurogenesis in 5 five familial Alzheimer's disease mutations (5XFAD) mice, an animal model for AD. In an in vitro thioflavin T assay, JWS showed a remarkable anti-Aβ aggregation effect. Histochemical analysis indicated that JWS had inhibitory effects on Aβ aggregation, Aβ-induced pathologies, and improved adult hippocampal neurogenesis in vivo. Taken together, these results suggest the therapeutic possibility of JWS for AD targeting Aβ aggregation, Aβ-mediated neurodegeneration, and impaired adult hippocampal neurogenesis.

Molecular topology and QSAR multi-target analysis to boost the in silico research for fungicides in agricultural chemistry

The aim of the present study is to show how molecular topology can be a powerful in silico tool for the prediction of the fungicidal activity of several diphenylamine derivatives against three fungal species (cucumber downy mildew, rice blast and cucumber gray mold). A multi-target QSAR model was developed, and two strategies were followed. First is the construction of a virtual library of molecules using DesMol2 program and a subsequent selection of potential active ones. Second is the selection of molecules from the literature on the basis of molecular scaffolds. More than 700 diphenylamine derivatives designed and other 60 fluazinam's derivatives with structural similarity higher than 80% were studied. Almost twenty percent of the molecules analyzed show potential activity against the three fungal species.