Bridging Molecular Docking to Molecular Dynamics in Exploring Ligand-Protein Recognition Process: An Overview

Vitamin D analog calcitriol for breast cancer therapy; an integrated drug discovery approach

As breast cancer remains leading cause of cancer death globally, it is essential to develop an affordable breast cancer therapy in underdeveloped countries. Drug repurposing offers potential to address gaps in breast cancer treatment. Molecular networking studies were performed for drug repurposing approach by using heterogeneous data. The PPI networks were built to select the target genes from the EGFR overexpression signaling pathway and its associated family members. The selected genes EGFR, ErbB2, ErbB4 and ErbB3 were allowed to interact with 2637 drugs, leads to PDI network construction of 78, 61, 15 and 19 drugs, respectively. As drugs approved for treating non cancer-related diseases or disorders are clinically safe, effective, and affordable, these drugs were given considerable attention. Calcitriol had shown significant binding affinities with all four receptors than standard neratinib. The RMSD, RMSF, and H-bond analysis of protein-ligand complexes from molecular dynamics simulation (100 ns), confirmed the stable binding of calcitriol with ErbB2 and EGFR receptors. In addition, MMGBSA and MMP BSA also affirmed the docking results. These in-silico results were validated with in-vitro cytotoxicity studies in SK-BR-3 and Vero cells. The IC50 value of calcitriol (43.07 mg/ml) was found to be lower than neratinib (61.50 mg/ml) in SK-BR-3 cells. In Vero cells the IC50 value of calcitriol (431.05 mg/ml) was higher than neratinib (404.95 mg/ml). It demonstrates that calcitriol suggestively downregulated the SK-BR-3 cell viability in a dose-dependent manner. These implications revealed calcitriol has shown better cytotoxicity and decreased the proliferation rate of breast cancer cells than neratinib.Communicated by Ramaswamy H. Sarma.

Natural product rhynchophylline prevents stress-induced hair graying by preserving melanocyte stem cells via the β2 adrenergic pathway suppression

Norepinephrine (NA), a stress hormone, can accelerate hair graying by binding to β2 adrenergic receptors (β2AR) on melanocyte stem cells (McSCs). From this, NA-β2AR axis could be a potential target for preventing the stress effect. However, identifying selective blockers for β2AR has been a key challenge. Therefore, in this study, advanced computer-aided drug design (CADD) techniques were harnessed to screen natural molecules, leading to the discovery of rhynchophylline as a promising compound. Rhynchophylline exhibited strong and stable binding within the active site of β2AR, as verified by molecular docking and dynamic simulation assays. When administered to cells, rhynchophylline effectively inhibited NA-β2AR signaling. This intervention resulted in a significant reduction of hair graying in a stress-induced mouse model, from 28.5% to 8.2%. To gain a deeper understanding of the underlying mechanisms, transcriptome sequencing was employed, which revealed that NA might disrupt melanogenesis by affecting intracellular calcium balance and promoting cell apoptosis. Importantly, rhynchophylline acted as a potent inhibitor of these downstream pathways. In conclusion, the study demonstrated that rhynchophylline has the potential to mitigate the negative impact of NA on melanogenesis by targeting β2AR, thus offering a promising solution for preventing stress-induced hair graying.

Mathematical modeling of cardio-oncology: Modeling the systemic effects of cancer therapeutics on the cardiovascular system

Cardiotoxicity is a common side-effect of many cancer therapeutics; however, to-date there has been very little push to understand the mechanisms underlying this group of pathologies. This has led to the emergence of cardio-oncology, a field of medicine focused on understanding the effects of cancer and its treatment on the human heart. Here, we describe how mechanistic modeling approaches have been applied to study open questions in the cardiovascular system and how these approaches are being increasingly applied to advance knowledge of the underlying effects of cancer treatments on the human heart. A variety of mechanistic, mathematical modeling techniques have been applied to explore the link between common cancer treatments, such as chemotherapy, radiation, targeted therapy, and immunotherapy, and cardiotoxicity, nevertheless there is limited coverage in the different types of cardiac dysfunction that may be associated with these treatments. Moreover, cardiac modeling has a rich heritage of mathematical modeling and is well suited for the further development of novel approaches for understanding the cardiotoxicities associated with cancer therapeutics. There are many opportunities to combine mechanistic, bottom-up approaches with data-driven, top-down approaches to improve personalized, precision oncology to better understand, and ultimately mitigate, cardiac dysfunction in cancer patients.

Exploring binding mode assessment of novel kaempferol, resveratrol, and quercetin derivatives with PPAR-α as potent drug candidates against cancer

Peroxisome proliferator-activated receptors (PPAR)-α, a ligand-activated transcription factor stands out to be a valuable protein target against cancer. Given that ligand binding is the crucial process for the activation of PPAR-α, fibrate class of synthetic compounds serves as potent agonist for the receptor. However, their serious side effects limit the long-term application in cancer. This emphasizes the dire need to identify new candidates that would exert desired activation by abrogating the adverse effects caused by synthetic agonists. Natural dietary products serve as an important source of drug discovery. Hence, the present study encompasses the investigation of the role of natural plant phenolic compounds: kaempferol, resveratrol, and quercetin and their 8708 derivatives by the means of computational pipeline comprising molecular docking and molecular dynamic (MD) simulation techniques. Docking calculations shortlisted potential candidates, namely 6-cinnamylchrysin (6-CC), resveratrol potassium-4-sulfate (RPS) and 6-[2-(3,4-Dihydroxyphenyl)-5-hydroxy-4-oxochromen-7-yl]oxyhexyl nitrate (DHOON), and derivatives of kaempferol, resveratrol, and quercetin, respectively. 6-CC, RPS, and DHOON manifested better affinities of - 32.83 kcal/mol (Ala333, Lys358, His440), - 27.22 kcal/mol (Tyr314, Met355), and - 30.18 kcal/mol (Ser280, Tyr314, Ala333), respectively, and were found to act as good stimulants for PPAR-α. Among these three compounds, 6-CC caused relatively least deviations and fluctuations analyzed through MD simulation which judiciously held responsible to attain most favorable interaction with PPAR-α. Followed by the binding free energy (ΔG) calculations using MM-GBSA confirmed the key role of 6-CC toward PPAR-α. The compound 6-CC also achieved high drug-likeness and pharmacokinetic properties. Thus, these findings stipulate new drug leads for PPAR-α receptor which abets a way to develop new anti-cancer drugs.

Cheminformatics identification of modulators of key carbohydrate-metabolizing enzymes from C. cujete for type-2 diabetes mellitus intervention

Purpose

The therapeutic use of oral hypoglycaemic agents in the management of type-2 diabetes mellitus (T2DM) is without adverse effects; thus, calls for alternative and novel candidates from natural products in medicinal plants.

Method

The study explored molecular docking and molecular dynamics (MD) simulation approaches to identify key antidiabetic metabolites from Crescentia cujete.

Results

Molecular docking results identified four and/or five best compounds against each target enzyme (alpha-glucosidase, dipeptidyl peptidase-IV, aldose reductase, and protein tyrosine phosphatase-1B (PTP-1B)) implicated in diabetes. The resulting complexes (except against PTP-1B) had higher docking scores above respective standards (acarbose, Diprotin A, ranirestat). The MD simulation results revealed compounds such as benzoic acid (-48.414 kcal/mol) and phytol (-45.112 kcal/mol) as well as chlorogenic acid (-42.978 kcal/mol) and naringenin (-31.292 kcal/mol) had higher binding affinities than the standards [acarbose (-28.248 kcal/mol), ranirestat (-21.042 kcal/mol)] against alpha-glucosidase and aldose reductase, respectively while Diprotin A (-45.112 kcal/mol) and ursolic acid (-18.740 kcal/mol) presented superior binding affinities than the compounds [luteolin (-41.957 kcal/mol and naringenin (-16.518 kcal/mol)] against DPP-IV and PTP-1B respectively.

Conclusion

While isoflavone (alpha-glucosidase), xylocaine (DPP-IV), luteolin (aldose reductase,) and chlorogenic acid (PTP-1B) were affirmed as the best inhibitors of respective enzyme targets, luteolin, and chlorogenic acid may be suggested and proposed as probable candidates against T2DM and related retinopathy complication based on their structural stability, compactness and affinity for three (DPP-IV, aldose reductase, and PTP-1B) of the four targets investigated. Further studies are warranted in vitro and in vivo on the antihyperglycaemic effects of these drug candidates.

Supplementary Information

The online version contains supplementary material available at 10.1007/s40200-023-01249-7.

Computational identification of potential inhibitors targeting cdk1 in colorectal cancer

Introduction: Despite improved treatment options, colorectal cancer (CRC) remains a huge public health concern with a significant impact on affected individuals. Cell cycle dysregulation and overexpression of certain regulators and checkpoint activators are important recurring events in the progression of cancer. Cyclin-dependent kinase 1 (CDK1), a key regulator of the cell cycle component central to the uncontrolled proliferation of malignant cells, has been reportedly implicated in CRC. This study aimed to identify CDK1 inhibitors with potential for clinical drug research in CRC. Methods: Ten thousand (10,000) naturally occurring compounds were evaluated for their inhibitory efficacies against CDK1 through molecular docking studies. The stability of the lead compounds in complex with CDK1 was evaluated using molecular dynamics simulation for one thousand (1,000) nanoseconds. The top-scoring candidates' ADME characteristics and drug-likeness were profiled using SwissADME. Results: Four hit compounds, namely, spiraeoside, robinetin, 6-hydroxyluteolin, and quercetagetin were identified from molecular docking analysis to possess the least binding scores. Molecular dynamics simulation revealed that robinetin and 6-hydroxyluteolin complexes were stable within the binding pocket of the CDK1 protein. Discussion: The findings from this study provide insight into novel candidates with specific inhibitory CDK1 activities that can be further investigated through animal testing, clinical trials, and drug development research for CRC treatment.

Thermal titration molecular dynamics (TTMD): shedding light on the stability of RNA-small molecule complexes

Ribonucleic acids are gradually becoming relevant players among putative drug targets, thanks to the increasing amount of structural data exploitable for the rational design of selective and potent binders that can modulate their activity. Mainly, this information allows employing different computational techniques for predicting how well would a ribonucleic-targeting agent fit within the active site of its target macromolecule. Due to some intrinsic peculiarities of complexes involving nucleic acids, such as structural plasticity, surface charge distribution, and solvent-mediated interactions, the application of routinely adopted methodologies like molecular docking is challenged by scoring inaccuracies, while more physically rigorous methods such as molecular dynamics require long simulation times which hamper their conformational sampling capabilities. In the present work, we present the first application of Thermal Titration Molecular Dynamics (TTMD), a recently developed method for the qualitative estimation of unbinding kinetics, to characterize RNA-ligand complexes. In this article, we explored its applicability as a post-docking refinement tool on RNA in complex with small molecules, highlighting the capability of this method to identify the native binding mode among a set of decoys across various pharmaceutically relevant test cases.

Pharmacophore mapping approach to find anti-cancer phytochemicals with metformin-like activities against transforming growth factor (TGF)-beta receptor I kinase: An in silico study

The most frequently prescribed first-line treatment for type II diabetes mellitus is metformin. Recent reports asserted that this diabetes medication can also shield users from cancer. Metformin induces cell cycle arrest in cancer cells. However, the exact mechanism by which this occurs in the cancer system is yet to be elucidated. Here, we investigated the impact of metformin on cell cycle arrest in cancer cells utilizing transforming growth factor (TGF)-beta pathway. TGF-ß pathway has significant effect on cell progression and growth. In order to gain an insight on the underlying molecular mechanism of metformin's effect on TGF beta receptor 1 kinase, molecular docking was performed. Metformin was predicted to interact with transforming growth factor (TGF)-beta receptor I kinase based on molecular docking and molecular dynamics simulations. Furthermore, pharmacophore was generated for metformin-TGF-ßR1 complex to hunt for novel compounds having similar pharmacophore as metformin with enhanced anti-cancer potentials. Virtual screening with 29,000 natural compounds from NPASS database was conducted separately for the generated pharmacophores in Ligandscout® software. Pharmacophore mapping showed 60 lead compounds for metformin-TGF-ßR1 complex. Molecular docking, molecular dynamics simulation for 100 ns and ADMET analysis were performed on these compounds. Compounds with CID 72473, 10316977 and 45140078 showed promising binding affinities and formed stable complexes during dynamics simulation with aforementioned protein and thus have potentiality to be developed into anti-cancer medicaments.

An insight into the cytotoxic, antimicrobial, antioxidant, and biocontrol perspective of novel Iron(III) complexes of substituted benzimidazoles: Inhibition kinetics and molecular simulations

Mononuclear complexes [FeCl3L2(OH2)] (L = L1, L2) were designed and synthesized by combining FeCl3 with 2-(3'-Aminophenylbenzimidazole) (L1) and 2-[(3'-N-Salicylidinephenyl)benzimidazole] (L2) and were characterized by physico-analytical strategies. The redox properties of the complexes were disclosed by the cyclic voltammetric method. Further, the interactions of complexes with proteins were studied by performing molecular docking engaging protein models of common cancer therapeutic targets to foresee their affinity to bind to these proteins. The complexes evidenced better protein-ligand docking (-8.4 and -9.0 kcal mol-1) and higher binding energies than their ligands. However, the L1 complex displayed improved binding free energy (-33.576 ± 1.01 kcal mol-1) compared to the other complexes and individual ligands. These compounds were screened for in vitro cytotoxic assays against triple-negative breast cancer cell lines (MDA-MB-468 cells), anti-inflammatory, antimicrobial, and antioxidant properties. The in vitro study complemented the in silico assay; therefore, these compounds may be a viable choice for expanding anticancer therapy. Additionally, the L2 showed better biocontrol activity owing to the enhanced growth of Trichoderma and inhibited the growth of Fusarium oxysporum.Communicated by Ramaswamy H. Sarma.

In Silico molecular docking and dynamic analysis of natural compounds against major non-structural proteins of SARS-COV-2

COVID-19 has infected millions and significantly affected the global economy and healthcare systems. Despite continuous lockdowns, symptomatic management with currently available medications, and numerous vaccination drives, it is still far more difficult to control. Against COVID-19 infection, the pressure to develop vaccines and drugs has led to using some currently available medications like remdesivir, azithromycin, hydroxychloroquine and ritonavir. Understanding the importance and potential of harmless molecules to tackle SARS-COV-2, we designed the present study to identify potential natural phytocompounds. In the present study, we docked natural compounds and standard drugs against SARS-COV-2 proteins: papain-like protease, main protease and helicase. ADME/T and ProTox-II analyses were used to determine the toxicity of phytocompounds and drugs. The docking analysis revealed that podophyllotoxin gave the highest binding affinity scores of -8.1, -7.1 and -7.4 kcal/mol against PLpro, Mpro and helicase, respectively. Among the control drugs, doxycycline hydrochloride showed the highest binding affinity of -10.5, -8.4 and -8.8 kcal/mol against PLpro, Mpro and helicase. The results of this study revealed that podophyllotoxin and doxycycline hydrochloride could be promising inhibitors against SARS-Cov-2. Molecular dynamic simulations were executed for the best docked (PLpro-podophyllotoxin) complex, and the results displayed stable conformation and convergence. Energy plot results predicted a global minima average energy of -95 kcal/mol and indicated podophyllotoxin's role in stabilizing protein and making it compact and complex. FarPPI server used MM/GBSA approach to determine free binding affinity, and helicase-gallic acid complex showed the highest affinity, respectively. Therefore, it can be concluded that there is still a need for in vitro and in vivo studies to support further and validate these findings and validate these findings.Communicated by Ramaswamy H. Sarma.

Design, Synthesis, and Biological Evaluation of Novel Quercetin Derivatives as PPAR-γ Partial Agonists by Modulating Epithelial-Mesenchymal Transition in Lung Cancer Metastasis

Epithelial-to-mesenchymal transition (EMT) is responsible for driving metastasis of multiple cancer types including lung cancer. Peroxisome proliferator-activated receptor (PPAR)-γ, a ligand-activated transcription factor, controls expression of variety of genes involved in EMT. Although several synthetic compounds act as potent full agonists for PPAR-γ, their long term application is restricted due to serious adverse effects. Therefore, partial agonists involving reduced and balanced PPAR-γ activity are more effective and valued. A previous study discerned the efficacy of quercetin and its derivatives to attain favorable stabilization with PPAR-γ. Here this work is extended by synthesizing five novel quercetin derivatives (QDs) namely thiosemicarbazone (QUETSC)) and hydrazones (quercetin isonicotinic acid hydrazone (QUEINH), quercetin nicotinic acid hydrazone (QUENH), quercetin 2-furoic hydrazone (QUE2FH), and quercetin salicyl hydrazone (QUESH)) and their effects are analyzed in modulating EMT in lung cancer cell lines via PPAR-γ partial activation. QDs-treated A549 cells diminish cell proliferation strongly at nanomolar concentration compared to NCI-H460 cells. Of the five screened derivatives, QUETSC, QUE2FH, and QUESH exhibit the property of partial activation as compared to the overexpressive level of rosiglitazone. Consistently, these QDs also suppress EMT process by markedly downregulating the levels of mesenchymal markers (Snail, Slug, and zinc finger E-box binding homeobox 1) and concomitant upregulation of epithelial marker (E-cadherin).

Binding characteristics of pyrrole-scaffold hepatitis B virus capsid inhibitors and identification of novel potent compounds

Hepatitis B virus (HBV) capsid assembly modulators (CAMs) are currently being evaluated in clinical trials as potential curative therapies for HBV. This study used in silico computational modeling to provide insights into the binding characteristics between the HBV core protein and two pyrrole-scaffold inhibitors, JNJ-6379 and GLP-26, both in the CAM-Normal (CAM-N) series. Molecular dynamics simulations showed that the pyrrole inhibitors displayed similar general binding-interaction patterns to NVR 3-778, another CAM-N, with hydrophobic interactions serving as the major driving force. However, consistent with their higher potency, the pyrrole inhibitors exhibited stronger nonpolar interactions with key residues in a solvent-accessible region as compared to NVR 3-778. This feature was facilitated by distinct hydrogen bond interactions of the pyrrole scaffold inhibitors with the residue 140 in chain B of the HBV core protein (L140B). Based on these findings, novel CAM-N compounds were designed to mimic the interaction with L140B residue while maximizing nonpolar interactions in the solvent-accessible region. Several 1H-pyrrole-2-carbonyl substituted pyrrolidine-based compounds with various hydrophobic side chains were synthesized and evaluated. Through analyses of the structure-activity and structure-druggability relations of a series of compounds, CU15 emerged as the most promising lead CAM-N compound, exhibiting sub-nanomolar potency and good pharmacokinetic profiles. Overall, the study demonstrated a practical approach to leverage computational methods for understanding key target binding features for rationale-based design, and for guiding the identification of novel compounds.

The use of Xuanbai Chengqi decoction on monkeypox disease through the estrone-target AR interaction

Introduction

After COVID-19, there was an outbreak of a new infectious disease caused by monkeypox virus. So far, no specific drug has been found to treat it. Xuanbai Chengqi decoction (XBCQD) has shown effects against a variety of viruses in China.

Methods

We searched for the active compounds and potential targets for XBCQD from multiple open databases and literature. Monkeypox related targets were searched out from the OMIM and GeneCards databases. After determining the assumed targets of XBCQD for monkeypox treatment, we built the PPI network and used R for GO enrichment and KEGG pathway analysis. The interactions between the active compounds and the hub targets were investigated by molecular docking and molecular dynamics (MD) simulations.

Results

In total, 5 active compounds and 10 hub targets of XBCQD were screened out. GO enrichment and KEGG analysis demonstrated that XBCQD plays a therapeutic role in monkeypox mainly by regulating signaling pathways related to viral infection and inflammatory response. The main active compound estrone binding to target AR was confirmed to be the best therapy choice for monkeypox.

Discussion

This study systematically explored the interactions between the bioactive compounds of XBCQD and the monkeypox-specific XBCQD targets using network pharmacological methods, bioinformatics analyses and molecular simulations, suggesting that XBCQD could have a beneficial therapeutic effect on monkeypox by reducing the inflammatory damage and viral replication via multiple pathways. The use of XBCQD on monkeypox disease was confirmed to be best worked through the estrone-target AR interaction. Our work could provide evidence and guidance for further research on the treatment of monkeypox disease.

Analysis of Delta(9) fatty acid desaturase gene family and their role in oleic acid accumulation in Carya cathayensis kernel

Carya cathayensis, commonly referred to as Chinese hickory, produces nuts that contain high-quality edible oils, particularly oleic acid (18:1). It is known that stearoyl-ACP desaturase (SAD) is the first key step converting stearic acid (C18:0, SA) to oleic acid (C18:1, OA) in the aminolevulinic acid (ALA) biosynthetic pathway and play an important role in OA accumulation. Thus far, there is little information about SAD gene family in C. cathayensis and the role of individual members in OA accumulation. This study searched the Chinese Hickory Genome Database and identified five members of SAD genes, designated as CcSADs, at the whole genome level through the comparison with the homologous genes from Arabidopsis. RNA-Seq analysis showed that CcSSI2-1, CcSSI2-2, and CcSAD6 were highly expressed in kernels. The expression pattern of CcSADs was significantly correlated with fatty acid accumulation during the kernel development. In addition, five full-length cDNAs encoding SADs were isolated from the developing kernel of C. cathayensis. CcSADs-green fluorescent protein (GFP) fusion construct was infiltrated into tobacco epidermal cells, and results indicated their chloroplast localization. The catalytic function of these CcSADs was further analyzed by heterologous expression in Saccharomyces cerevisiae, Nicotiana benthamiana, and walnut. Functional analysis demonstrated that all CcSADs had fatty acid desaturase activity to catalyze oleic acid biosynthesis. Some members of CcSADs also have strong substrate specificity for 16:0-ACP to synthesize palmitoleic acid (C16:1, PA). Our study documented SAD gene family in C. cathayensis and the role of CcSSI2-1, CcSSI2-2, and CcSAD6 in OA accumulation, which could be important for future improvement of OA content in this species via genetic manipulation.

Targeted Protein Degradation: Advances, Challenges, and Prospects for Computational Methods

The therapeutic approach of targeted protein degradation (TPD) is gaining momentum due to its potentially superior effects compared with protein inhibition. Recent advancements in the biotech and pharmaceutical sectors have led to the development of compounds that are currently in human trials, with some showing promising clinical results. However, the use of computational tools in TPD is still limited, as it has distinct characteristics compared with traditional computational drug design methods. TPD involves creating a ternary structure (protein-degrader-ligase) responsible for the biological function, such as ubiquitination and subsequent proteasomal degradation, which depends on the spatial orientation of the protein of interest (POI) relative to E2-loaded ubiquitin. Modeling this structure necessitates a unique blend of tools initially developed for small molecules (e.g., docking) and biologics (e.g., protein-protein interaction modeling). Additionally, degrader molecules, particularly heterobifunctional degraders, are generally larger than conventional small molecule drugs, leading to challenges in determining drug-like properties like solubility and permeability. Furthermore, the catalytic nature of TPD makes occupancy-based modeling insufficient. TPD consists of multiple interconnected yet distinct steps, such as POI binding, E3 ligase binding, ternary structure interactions, ubiquitination, and degradation, along with traditional small molecule properties. A comprehensive set of tools is needed to address the dynamic nature of the induced proximity ternary complex and its implications for ubiquitination. In this Perspective, we discuss the current state of computational tools for TPD. We start by describing the series of steps involved in the degradation process and the experimental methods used to characterize them. Then, we delve into a detailed analysis of the computational tools employed in TPD. We also present an integrative approach that has proven successful for degrader design and its impact on project decisions. Finally, we examine the future prospects of computational methods in TPD and the areas with the greatest potential for impact.

Antioxidant and Anti-Glycation Potential of H2 Receptor Antagonists-In Vitro Studies and a Systematic Literature Review

Background: Histamine H2 receptor antagonists are a group of drugs that inhibit gastric juice secretion in gastrointestinal diseases. However, there is evidence to suggest that H2 blockers have a broader spectrum of activity. The antioxidant properties of H2 blockers have not been fully elucidated, and their anti-glycation potential has not been studied to date. Therefore, this is the first study to compare the antioxidant and antiglycation potentials of the most popular H2 antagonists (ranitidine, cimetidine, and famotidine) on protein glycoxidation in vitro. Methods: Bovine serum albumin (BSA) was glycated using sugars (glucose, fructose, galactose, and ribose) as well as aldehydes (glyoxal and methylglyoxal). Results: In the analyzed group of drugs, ranitidine was the only H2 blocker that significantly inhibited BSA glycation in all tested models. The contents of protein carbonyls, protein glycoxidation products (↓dityrosine, ↓N-formylkynurenine), and early (↓Amadori products) and late-stage (↓AGEs) protein glycation products decreased in samples of glycated BSA with the addition of ranitidine relative to BSA with the addition of the glycating agents. The anti-glycation potential of ranitidine was comparable to those of aminoguanidine and Trolox. In the molecular docking analysis, ranitidine was characterized by the lowest binding energy for BSA sites and could compete with protein amino groups for the addition of carbonyl groups. H2 blockers also scavenge free radicals. The strongest antioxidant properties are found in ranitidine, which additionally has the ability to bind transition metal ions. The systematic literature review also revealed that the anti-glycation effects of ranitidine could be attributed to its antioxidant properties. Conclusions: Ranitidine showed anti-glycation and antioxidant properties. Further research is needed, particularly in patients with diseases that promote protein glycation.

Preclinical Evaluation of Novel PET Probes for Dementia

The development of novel PET imaging agents that selectively bind specific dementia-related targets can contribute significantly to accurate, differential and early diagnosis of dementia causing diseases and support the development of therapeutic agents. Consequently, in recent years there has been a growing body of literature describing the development and evaluation of potential new promising PET tracers for dementia. This review article provides a comprehensive overview of novel dementia PET probes under development, classified by their target, and pinpoints their preclinical evaluation pathway, typically involving in silico, in vitro and ex/in vivo evaluation. Specific target-associated challenges and pitfalls, requiring extensive and well-designed preclinical experimental evaluation assays to enable successful clinical translation and avoid shortcomings observed for previously developed 'well-established' dementia PET tracers are highlighted in this review.

In Silico Analysis of Pyeongwi-San Involved in Inflammatory Bowel Disease Treatment Using Network Pharmacology, Molecular Docking, and Molecular Dynamics

BACKGOUND

Pyeongwi-san (PWS) is a widely used formula for treating digestive disorders in Korea and China. Inflammatory bowel disease (IBD) is characterized by progressive inflammation of the gastrointestinal tract. Emerging evidence supports the protective effect of PWS against IBD, but specific mechanisms are still elusive.

METHODS

Active compounds of PWS were screened from the medicinal materials and chemical compounds in Northeast Asian traditional medicine (TM-MC) in the consideration of drug-likeness and oral bioavailability. Target candidates of active compounds were predicted using the ChEMBL database. IBD-related targets were obtained from the GeneCards and DisGeNET databases. The network of composition-targets-disease was constructed. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment were analyzed. Molecular docking was used to simulate the binding affinity of active compounds on target proteins and molecular dynamics was used to validate the molecular docking result.

RESULTS

A total of 26 core target proteins of PWS were related to IBD. Enrichment analysis suggested that PWS is highly associated with tumor necrosis factor signaling pathway, apoptosis, and the collapse of tight junctions. Moreover, molecular docking and molecular dynamics simulation proposed β-eudesmol and (3R,6R,7S)-1,10-bisaboladien-3-ol to ameliorate IBD through the binding to TNF and MMP9, respectively.

CONCLUSION

Present in silico analysis revealed potential pathways and insight of PWS to regulate IBD. These results imply that the therapeutic effect of PWS might be achieved via an inhibitory effect.

Fighting Antimicrobial Resistance: Insights on How the Staphylococcus aureus NorA Efflux Pump Recognizes 2-Phenylquinoline Inhibitors by Supervised Molecular Dynamics (SuMD) and Molecular Docking Simulations

The superbug Staphylococcus aureus (S. aureus) exhibits several resistance mechanisms, including efflux pumps, that strongly contribute to antimicrobial resistance. In particular, the NorA efflux pump activity is associated with S. aureus resistance to fluoroquinolone antibiotics (e.g., ciprofloxacin) by promoting their active extrusion from cells. Thus, since efflux pump inhibitors (EPIs) are able to increase antibiotic concentrations in bacteria as well as restore their susceptibility to these agents, they represent a promising strategy to counteract bacterial resistance. Additionally, the very recent release of two NorA efflux pump cryo-electron microscopy (cryo-EM) structures in complex with synthetic antigen-binding fragments (Fabs) represents a real breakthrough in the study of S. aureus antibiotic resistance. In this scenario, supervised molecular dynamics (SuMD) and molecular docking experiments were combined to investigate for the first time the molecular mechanisms driving the interaction between NorA and efflux pump inhibitors (EPIs), with the ultimate goal of elucidating how the NorA efflux pump recognizes its inhibitors. The findings provide insights into the dynamic NorA-EPI intermolecular interactions and lay the groundwork for future drug discovery efforts aimed at the identification of novel molecules to fight antimicrobial resistance.

The Art of War with Pseudomonas aeruginosa: Targeting Mex Efflux Pumps Directly to Strategically Enhance Antipseudomonal Drug Efficacy

Pseudomonas aeruginosa (P. aeruginosa) poses a grave clinical challenge due to its multidrug resistance (MDR) phenotype, leading to severe and life-threatening infections. This bacterium exhibits both intrinsic resistance to various antipseudomonal agents and acquired resistance against nearly all available antibiotics, contributing to its MDR phenotype. Multiple mechanisms, including enzyme production, loss of outer membrane proteins, target mutations, and multidrug efflux systems, contribute to its antimicrobial resistance. The clinical importance of addressing MDR in P. aeruginosa is paramount, and one pivotal determinant is the resistance-nodulation-division (RND) family of drug/proton antiporters, notably the Mex efflux pumps. These pumps function as crucial defenders, reinforcing the emergence of extensively drug-resistant (XDR) and pandrug-resistant (PDR) strains, which underscores the urgency of the situation. Overcoming this challenge necessitates the exploration and development of potent efflux pump inhibitors (EPIs) to restore the efficacy of existing antipseudomonal drugs. By effectively countering or bypassing efflux activities, EPIs hold tremendous potential for restoring the antibacterial activity against P. aeruginosa and other Gram-negative pathogens. This review focuses on concurrent MDR, highlighting the clinical significance of efflux pumps, particularly the Mex efflux pumps, in driving MDR. It explores promising EPIs and delves into the structural characteristics of the MexB subunit and its substrate binding sites.

Computational insight into stability-enhanced systems of anthocyanin with protein/peptide

Anthocyanins, which belong to the flavonoid group, are commonly found in the organs of plants native to South and Central America. However, these pigments are unstable under conditions of varying pH, heat, etc., which limits their potential applications. One method for preserving the stability of anthocyanins is through encapsulation using proteins or peptides. Nevertheless, the complex and diverse structure of these molecules, as well as the limitation of experimental technologies, have hindered a comprehensive understanding of the encapsulation processes and the mechanisms by which stability is enhanced. To address these challenges, computational methods, such as molecular docking and molecular dynamics simulation have been used to study the binding affinity and dynamics of interactions between proteins/peptides and anthocyanins. This review summarizes the mechanisms of interaction between these systems, based on computational approaches, and highlights the role of proteins and peptides in the stability enhancement of anthocyanins. It also discusses the current limitations of these methods and suggests possible solutions.

Phytoestrogen-derived multifunctional ligands for targeted therapy of breast cancer

Nano-targeted delivery systems have been widely used for breast tumor drug delivery. Estrogen receptors are considered to be significant drug delivery target receptors due to their overexpression in a variety of tumor cells. However, targeted ligands have a significant impact on the safety and effectiveness of active delivery systems, limiting the clinical transformation of nanoparticles. Phytoestrogens have shown good biosafety characteristics and some affinity with the estrogen receptor. In the present study, molecular docking was used to select tanshinone IIA (Tan IIA) among phytoestrogens as a target ligand to be used in nanodelivery systems with some modifications. Modified Tan IIA (Tan-NH2) showed a good biosafety profile and demonstrated tumor-targeting, anti-tumor and anti-tumor metastasis effects. Moreover, the ligand was utilized with the anti-tumor drug Dox-loaded mesoporous silica nanoparticles via chemical modification to generate a nanocomposite Tan-Dox-MSN. Tan-Dox-MSN had a uniform particle size, good dispersibility and high drug loading capacity. Validation experiments in vivo and in vitro showed that it also had a better targeting ability, anti-tumor effect and lower toxicity in normal organs. These results supported the idea that phytoestrogens with high affinity for the estrogen receptor could improve the therapeutic efficacy of nano-targeted delivery systems in breast tumors.

Biochemical Targets and Molecular Mechanism of Matrine against Aging

The aim of this study is to explore the potential targets and molecular mechanism of matrine (MAT) against aging. Bioinformatic-based network pharmacology was used to investigate the aging-related targets and MAT-treated targets. A total of 193 potential genes of MAT against aging were obtained and then the top 10 key genes (cyclin D1, cyclin-dependent kinase 1, Cyclin A2, androgen receptor, Poly [ADP-ribose] polymerase-1 (PARP1), histone-lysine N-methyltransferase, albumin, mammalian target of rapamycin, histone deacetylase 2, and matrix metalloproteinase 9) were filtered by the molecular complex detection, maximal clique centrality (MMC) algorithm, and degree. The Metascape tool was used for analyzing biological processes and pathways of the top 10 key genes. The main biological processes were response to an inorganic substance and cellular response to chemical stress (including cellular response to oxidative stress). The major pathways were involved in cellular senescence and the cell cycle. After an analysis of major biological processes and pathways, it appears that PARP1/nicotinamide adenine dinucleotide (NAD⁺)-mediated cellular senescence may play an important role in MAT against aging. Molecular docking, molecular dynamics simulation, and in vivo study were used for further investigation. MAT could interact with the cavity of the PARP1 protein with the binding energy at -8.5 kcal/mol. Results from molecular dynamics simulations showed that the PARP1-MAT complex was more stable than PARP1 alone and that the binding-free energy of the PARP1-MAT complex was -15.962 kcal/mol. The in vivo study showed that MAT could significantly increase the NAD⁺ level of the liver of d-gal-induced aging mice. Therefore, MAT could interfere with aging through the PARP1/NAD⁺-mediated cellular senescence signaling pathway.

Molecular docking in organic, inorganic, and hybrid systems: a tutorial review

Molecular docking simulation is a very popular and well-established computational approach and has been extensively used to understand molecular interactions between a natural organic molecule (ideally taken as a receptor) such as an enzyme, protein, DNA, RNA and a natural or synthetic organic/inorganic molecule (considered as a ligand). But the implementation of docking ideas to synthetic organic, inorganic, or hybrid systems is very limited with respect to their use as a receptor despite their huge popularity in different experimental systems. In this context, molecular docking can be an efficient computational tool for understanding the role of intermolecular interactions in hybrid systems that can help in designing materials on mesoscale for different applications. The current review focuses on the implementation of the docking method in organic, inorganic, and hybrid systems along with examples from different case studies. We describe different resources, including databases and tools required in the docking study and applications. The concept of docking techniques, types of docking models, and the role of different intermolecular interactions involved in the docking process to understand the binding mechanisms are explained. Finally, the challenges and limitations of dockings are also discussed in this review.

Graphical abstract

Exploring the structural, photophysical and optoelectronic properties of a diaryl heptanoid curcumin derivative and identification as a SARS-CoV-2 inhibitor

Developing modifiable natural products those having antiviral activities against SARS-CoV-2 is a key research area which is popular in current scenario of COVID pandemic. A diaryl heptanoid curcumin and its derivatives are already presenting promising candidates for anti-viral drug development. We have synthesized single crystals of a dimethylamino derivative of natural curcumin and structural characterization was done by single crystal XRD analysis. Using steady-state absorption and emission spectra and guided by complimentary ab initio calculations, we unraveled the solvent effects on the photophysical properties of the dimethyl amino curcumin derivative. Chemical reactivity of the compound has investigated using frontier molecular orbitals and molecular electrostatic potential surface. High stability of the curcumin derivative in water environment has evaluated by Radial Distributions Functions (RDF) calculated via Molecular Dynamics (MD) simulations. The inhibitory activity of the title compound was evaluated by in silico methods and the stability of the protein-ligand complexes were studied using Molecular Dynamics simulations and MM-PBSA analysis. With this detailed study, we hope to motivate scientific community to develop new curcumin derivatives against SARS-CoV-2 virus.

Updates on drug designing approach through computational strategies: a review

The drug discovery and development (DDD) process in pursuit of novel drug candidates is a challenging procedure requiring lots of time and resources. Therefore, computer-aided drug design (CADD) methodologies are used extensively to promote proficiency in drug development in a systematic and time-effective manner. The point in reference is SARS-CoV-2 which has emerged as a global pandemic. In the absence of any confirmed drug moiety to treat the infection, the science fraternity adopted hit and trial methods to come up with a lead drug compound. This article is an overview of the virtual methodologies, which assist in finding novel hits and help in the progression of drug development in a short period with a specific medicinal solution.

Molecular mechanisms augmenting resistance to current therapies in clinics among cervical cancer patients

Cervical cancer (CC) is the fourth leading cause of cancer death (~ 324,000 deaths annually) among women internationally, with 85% of these deaths reported in developing regions, particularly sub-Saharan Africa and Southeast Asia. Human papillomavirus (HPV) is considered the major driver of CC, and with the availability of the prophylactic vaccine, HPV-associated CC is expected to be eliminated soon. However, female patients with advanced-stage cervical cancer demonstrated a high recurrence rate (50-70%) within two years of completing radiochemotherapy. Currently, 90% of failures in chemotherapy are during the invasion and metastasis of cancers related to drug resistance. Although molecular target therapies have shown promising results in the lab, they have had little success in patients due to the tumor heterogeneity fueling resistance to these therapies and bypass the targeted signaling pathway. The last two decades have seen the emergence of immunotherapy, especially immune checkpoint blockade (ICB) therapies, as an effective treatment against metastatic tumors. Unfortunately, only a small subgroup of patients (< 20%) have benefited from this approach, reflecting disease heterogeneity and manifestation with primary or acquired resistance over time. Thus, understanding the mechanisms driving drug resistance in CC could significantly improve the quality of medical care for cancer patients and steer them to accurate, individualized treatment. The rise of artificial intelligence and machine learning has also been a pivotal factor in cancer drug discovery. With the advancement in such technology, cervical cancer screening and diagnosis are expected to become easier. This review will systematically discuss the different tumor-intrinsic and extrinsic mechanisms CC cells to adapt to resist current treatments and scheme novel strategies to overcome cancer drug resistance.

Circulating Soluble Urokinase Plasminogen Activator Receptor as a Predictive Indicator for COVID-19-Associated Acute Kidney Injury and Mortality: Clinical and Bioinformatics Analysis

Urokinase receptors regulate the interplay between inflammation, immunity, and blood clotting. The soluble urokinase plasminogen activator system is an immunologic regulator affecting endothelial function and its related receptor; the soluble urokinase plasminogen activator receptor (suPAR) has been reported to impact kidney injury. This work aims to measure serum levels of suPAR in COVID-19 patients and correlate the measurements with variable clinicolaboratory parameters and patient outcomes. In this prospective cohort study, 150 COVID-19 patients and 50 controls were included. The circulating suPAR levels were quantified by Enzyme-linked immunosorbent assay (ELISA). Routine COVID-19 laboratory assessments, including CBC, CRP, LDH, serum creatinine, and estimated glomerular filtration rates, were performed. The need for oxygen therapy, CO-RAD score, and survival rates was assessed. Bioinformatic analysis and molecular docking were run to explore the urokinase receptor structure/function and to characterize molecules as potential anti-suPAR therapeutic targets, respectively. We found higher circulating suPAR levels in COVID-19 patients vs. controls (p < 0.001). Circulating suPAR levels positively correlated with COVID-19 severity, the need for O₂ therapy, the total leukocytes count, and the neutrophils to lymphocyte ratio, while they were negatively correlated with the O₂ saturation level, albumin, blood calcium, lymphocytic count, and GFR. In addition, the suPAR levels were associated with poor prognostic outcomes such as a high incidence of acute kidney injury (AKI) and mortality rate. Kaplan-Meier curves showed a lower survival rate with higher suPAR levels. The logistic regression analysis confirmed the significant association of suPAR levels with the occurrence of AKI related to COVID-19 and with increased mortality probability within three months of COVID-19 follow-up. Some compounds that can act similarly to uPAR were discovered and tested by molecular docking to identify the possible ligand-protein interactions. In conclusion, higher circulating suPAR levels were associated with COVID-19 severity and could be considered a putative predictor of AKI development and mortality.

Investigation of the effects of porosity and volume fraction on the atomic behavior of cancer cells and microvascular cells of 3DN5 and 5OTF macromolecular structures during hematogenous metastasis using the molecular dynamics method

BACKGROUND AND OBJECTIVE

The molecular dynamics (MD) simulation is a powerful tool for researching how cancer patients are treated. The efficiency of many factors may be predicted using this approach in great detail and with atomic accuracy.

METHODS

The MD simulation method was used to investigate the impact of porosity and the number of cancer cells on the atomic behavior of cancer cells during the hematogenous spread. In order to examine the stability of simulated structures, temperature and potential energy (PE) values are used. To evaluate how cell structure has changed, physical parameters such as gyration radius, interaction force, and interaction energy are also used.

RESULTS

The findings demonstrate that the samples' gyration radius, interaction energy, and interaction force rose from 41.33 Å, -551.38 kcal/mol, and -207.10 kcal/mol Å to 49.49, -535.94 kcal/mol, and -190.05 kcal/mol Å, respectively, when the porosity grew from 0% to 5%. Also, the interaction energy and force in the samples fell from -551.38 kcal/mol and -207.10 kcal/mol to -588.03 kcal/mol and -237.81 kcal/mol Å, and the amount of gyration radius reduced from 41.33 to 37.14 Å as the number of cancer cells rose from 1 to 5 molecules. The strength and stability of the simulated samples will improve when the radius of gyration is decreased.

CONCLUSIONS

Therefore, high accumulation of cancer cells will make them resistant to atomic collapse. It is expected that the results of this simulation should be used to optimize cancer treatment processes further.

An overview of compound properties, multiparameter optimization, and computational drug design methods for PARP-1 inhibitor drugs

Breast cancer treatment with PARP-1 inhibitors remains challenging due to emerging toxicities, drug resistance, and unaffordable costs of treatment options. How do we invent strategies to design better anti-cancer drugs? A part of the answer is in optimized compound properties, desirability functions, and modern computational drug design methods that drive selectivity and toxicity and have not been reviewed for PARP-1 inhibitors. Nonetheless, comparisons of these compound properties for PARP-1 inhibitors are not available in the literature. In this review, we analyze the physchem, PKPD space to identify inherent desirability functions characteristic of approved drugs that can be valuable for the design of better candidates. Recent literature utilizing ligand, structure-based drug design strategies and matched molecular pair analysis (MMPA) for the discovery of novel PARP-1 inhibitors are also reviewed. Thus, this perspective provides valuable insights into the medchem and multiparameter optimization of PARP-1 inhibitors that might be useful to other medicinal chemists.

Evaluation of autophagy inhibition to combat cancer: (vanadium complex)-protein interactions, parameterization, and validation of a new force field

Autophagy has drawn attention from the scientific community, mainly because of its significant advantages over chemotherapeutic processes. One of these advantages is its direct action on cancer cells, avoiding possible side effects, unlike chemotherapy, which reaches tumor cells and affects healthy cells in the body, leading to a great loss in the quality of life of patients. In this way, it is known that vanadium complex (VC) [VO(oda)(phen)] has proven inhibition effect on autophagy process in pancreatic cancer cells. Keeping that in mind, molecular dynamics (MD) simulations can be considered excellent strategies to investigate the interaction of metal complexes and their biological targets. However, simulations of this type are strongly dependent on the appropriate choice of force field (FF). Therefore, this work proposes the development of AMBER FF parameters for VC, having a minimum energy structure as a starting point, obtained through DFT calculations with B3LYP/def2-TZVP level of theory plus ECP for the vanadium atom. An MD simulation in vacuum was performed to validate the developed FF. From the structural analyses, satisfying values of VC bond lengths and angles were obtained, where a good agreement with the experimental data and the quantum reference was found. The RMSD analysis showed an average of only 0.3%. Finally, we performed docking and MD (120 ns) simulations with explicit solvent between VC and PI3K. Overall, our findings encourage new parameterizations of metal complexes with significant biological applications, as well as allow to contribute to the elucidation of the complex process of autophagy.

In Silico Analyses of a Promising Drug Candidate for the Treatment of Amyotrophic Lateral Sclerosis Targeting Superoxide Dismutase I Protein

Amyotrophic lateral sclerosis (ALS) is the most prevalent motor neuron disorder in adults, which is associated with a highly disabling condition. To date, ALS remains incurable, and the only drugs approved by the FDA for its treatment confer a limited survival benefit. Recently, SOD1 binding ligand 1 (SBL-1) was shown to inhibit in vitro the oxidation of a critical residue for SOD1 aggregation, which is a central event in ALS-related neurodegeneration. In this work, we investigated the interactions between SOD1 wild-type and its most frequent variants, i.e., A4V (NP_000445.1:p.Ala5Val) and D90A (NP_000445.1:p.Asp91Val), with SBL-1 using molecular dynamics (MD) simulations. The pharmacokinetics and toxicological profile of SBL-1 were also characterized in silico. The MD results suggest that the complex SOD1-SBL-1 remains relatively stable and interacts within a close distance during the simulations. This analysis also suggests that the mechanism of action proposed by SBL-1 and its binding affinity to SOD1 may be preserved upon mutations A4V and D90A. The pharmacokinetics and toxicological assessments suggest that SBL-1 has drug-likeness characteristics with low toxicity. Our findings, therefore, suggested that SBL-1 may be a promising strategy to treat ALS based on an unprecedented mechanism, including for patients with these frequent mutations.

Synthesis and biological evaluation of substituted acetamide derivatives as potential butyrylcholinestrase inhibitors

Alzheimer's disease (AD) is the most common type of age-related dementia. Inhibition of butyrylcholinesterase (BChE) emerge as an effective therapeutic target for AD. A series of new substituted acetamide derivatives were designed, synthesized and evaluated for their ability to inhibit BChE. The bioassay results revealed that several compounds displayed attractive inhibition against BChE). Among them, compound 8c exhibited the highest BChE inhibition with IC₅₀ values of 3.94 μM. Lineweaver Burk plot indicated that 8c acted as a mixed-type BChE inhibitor. In addition, docking studies confirmed the results obtained through in vitro experiments, and showed that 8c bound to the catalytic anionic site (CAS) and peripheral anionic site (PAS) of BChE active site. Meanwhile, its ADME parameters were approximated using in silico method. Molecular dynamics simulation studies on the complex of 8c-BChE were performed, RMSD, RMSF, Rg, SASA, and the number of hydrogen bonds were calculated as well. These results implied that 8c could serve as appropriate lead molecule for the development of BChE inhibitor.

Exploring the mechanism of action of Hedyotis diffusa Willd on acne using network analysis

In this study, we used a network pharmacological method to explore the active ingredients of Hedyotis diffusa Willd (HDW) in the treatment of acne and elucidated the physiological mechanisms in the human body in which they are involved. We identified the active compounds of HDW that are expected to act effectively in the human body using the Traditional Chinese Medicine Systems Pharmacology database and analysis platform and extracted potential interacting proteins for each active compound using the Swiss Target Prediction platform. Next, we analyzed the potential mechanisms of action of the protein targets shared by HDW and each standard drug on acne and assessed the possibility of spontaneous occurrence of the binding between proteins and active compounds through the molecular docking process. Seven active compounds were selected according to the oral bioavailability and drug-likeness criteria of the Traditional Chinese Medicine Systems Pharmacology database and analysis platform. Subsequently, 300 protein targets were collected from the Swiss Target Prediction. Using the Search Tool for the Retrieval of Interacting Genes/Proteins database, a protein-protein interaction network was constructed by analyzing the relationship between HDW, acne, and each standard drug. By analyzing the gene ontology terms and Kyoto Encyclopedia of Genes and Genomes pathway, the "positive regulation of lipid metabolic process" was found to be the most involved pathway shared by HDW, acne, and isotretinoin. An analysis of the protein targets shared by the antibiotic agents with HDW and acne found that "cholesterol storage" in tetracycline, "icosacoid transport" in azithromycin, "steroid hydroxylase activity" in erythromycin, "positive regulation of leukocyte tethering or rolling" in clindamycin, "response to UV-A" in minocycline, "steroid 11-beta-monooxygenase activity" in doxycycline, and "neutrophil-mediated immunity" in trimethoprim were the most involved. Virtual molecular docking analysis showed that all proteins spontaneously bound to their corresponding active compounds. Our analysis suggests that HDW can, directly and indirectly, suppress sebum secretion and exert antiinflammatory effects on acne. Further, HDW may regulate free radicals and suppress apoptosis. Therefore, HDW can be used as an alternative or supplement to standard drugs for acne treatment in patients who cannot use standard treatments due to side effects.

In silico repurposing of CNS drugs for multiple sclerosis

Multiple sclerosis (MS) is an autoimmune neurodegenerative disease affecting numerous people worldwide. While the relapsing subtypes of MS are to some extent treatable, the disease remains incurable leading to progressive disability. Limited efficacy of current small molecule drugs necessitates development of efficient and safe MS medications. Accordingly, drug repurposing is an invaluable strategy that recognizes new targets for known drugs especially in the field of poorly addressed therapeutic areas. Drug discovery largely depends on the identification of potential binding molecules to the intended biomolecular target(s). In this regard, current study was devoted to in silico repurposing of 263 small molecule CNS drugs to achieve superior binders to some MS-related targets. On the basis of molecular docking scores, thioxanthene and benzisothiazole-based antipsychotics could be identified as potential binders to sphingosine-1-phosphate lyase (S1PL) and cyclophilin D (CypD). Tightest interaction modes were observed for zuclopenthixol-S1PL (ΔG_b -7.96 kcal/mol) and lurasidone-CypD (ΔG_b -8.84 kcal/mol) complexes. Molecular dynamics (MD) simulations proved the appropriate and stable accommodation of top-ranked drugs inside enzyme binding sites during 100 ns. Hydroxyethyl piperazine of zuclopenthixol and benzisothiazole of lurasidone flipped inside the binding pocket to interact with adjacent polar and apolar residues. Solvent accessible surface area (SASA) fluctuations confirmed the results of binding trajectory analysis and showed that non-polar hydrophobic interactions played significant roles in acquired stabilities. Our results on lurasidone binding pattern were interestingly in accordance with previous reports on X-ray structures of other norbornane maleimide derivatives as CypD inhibitors. According to this, Asn144, Phe102 and Phe155 served as important residues in providing stable binding pose of lurasidone through both exo and endo conformations. Although experimental results are necessary to be achieved, the outcomes of this study proposed the potentiality of some thioxanthene and benzisothiazole-based antipsychotics for binding to S1PL and CypD, respectively, as MS-related targets.

Parsing structural fragments of thiazolidin-4-one based α-amylase inhibitors: A combined approach employing in vitro colorimetric screening and GA-MLR based QSAR modelling supported by molecular docking, molecular dynamics simulation and ADMET studies

α-Amylase (EC.3.2.1.1) is a ubiquitous digestive endoamylase. The abrupt rise in blood glucose levels due to the hydrolysis of carbohydrates by α-amylase at a faster rate is one of the main reasons for type 2 diabetes. The inhibitors prevent the action of digestive enzymes, slowing the digestion of carbs and eventually assisting in the management of postprandial hyperglycemia. In the course of developing α-amylase inhibitors, we have screened 2-aryliminothiazolidin-4-one based analogs for their in vitro α-amylase inhibitory potential and employed various in silico approaches for the detailed exploration of the bioactivity. The DNSA bioassay revealed that compounds 5c, 5e, 5h, 5j, 5m, 5o and 5t were more potent than the reference drug (IC₆₀ value = 22.94 ± 0.24 μg mL^-1). The derivative 5o with -NO₂ group at both the rings was the most potent analog with an IC₆₀ value of 19.67 ± 0.20 μg mL^-1 whereas derivative 5a with unsubstituted aromatic rings showed poor inhibitory potential with an IC₆₀ value of 33.40 ± 0.15 μg mL^-1. The reliable QSAR models were developed using the QSARINS software. The high value of R²_ext = 0.9632 for model IM-9 showed that the built model can be applied to predict the α-amylase inhibitory activity of the untested molecules. A consensus modelling approach was also employed to test the reliability and robustness of the developed QSAR models. Molecular docking and molecular dynamics were employed to validate the bioassay results by studying the conformational changes and interaction mechanisms. A step further, these compounds also exhibited good ADMET characteristics and bioavailability when tested for in silico pharmacokinetics prediction parameters.

In silico analysis prediction of HepTH1-5 as a potential therapeutic agent by targeting tumour suppressor protein networks

Many studies reported that the activation of tumour suppressor protein, p53 induced the human hepcidin expression. However, its expression decreased when p53 was silenced in human hepatoma cells. Contrary to Tilapia hepcidin TH1-5, HepTH1-5 was previously reported to trigger the p53 activation through the molecular docking approach. The INhibitor of Growth (ING) family members are also shown to directly interact with p53 and promote cell cycle arrest, senescence, apoptosis and participate in DNA replication and DNA damage responses to suppress the tumour initiation and progression. However, the interrelation between INGs and HepTH1-5 remains unknown. Therefore, this study aims to identify the mechanism and their protein interactions using in silico approaches. The finding revealed that HepTH1-5 and its ligands had interacted mostly on hotspot residues of ING proteins which involved in histone modifications via acetylation, phosphorylation, and methylation. This proves that HepTH1-5 might implicate in an apoptosis signalling pathway and preserve the protein structure and function of INGs by reducing the perturbation of histone binding upon oxidative stress response. This study would provide theoretical guidance for the design and experimental studies to decipher the role of HepTH1-5 as a potential therapeutic agent for cancer therapy. Communicated by Ramaswamy H. Sarma.

Structural Dynamics-Driven Discovery of Anticancer and Antimetastatic Effects of Diltiazem and Glibenclamide Targeting Urokinase Receptor

Diltiazem and glibenclamide are commonly used hypotensive and antidiabetic drugs. This study reports the discovery of the potential antitumor and antimetastatic effects of these two drugs using a structural dynamics-driven virtual screening targeting urokinase receptor (uPAR). Owing to uPAR's high flexibility, currently resolved crystal structures of uPAR, all in ligand-bound states, provide limited representations of its physiological conformation. To improve the accuracy of screening, we performed a long-timescale molecular dynamics simulation and obtained the representative conformations of apo-uPAR as the targets for our screening. Experimentally, we demonstrated that diltiazem and glibenclamide bound uPAR with K_D values in the micromolar range. In addition, both compounds effectively suppressed tumor growth and metastasis in a uPAR-dependent manner in vitro and in vivo. This work not only provides two potent uPAR inhibitors but also reports a proof-of-concept study on the potential off-label antitumor and antimetastatic uses of diltiazem and glibenclamide.

Lessons Learnt from COVID-19: Computational Strategies for Facing Present and Future Pandemics

Since its outbreak in December 2019, the COVID-19 pandemic has caused the death of more than 6.5 million people around the world. The high transmissibility of its causative agent, the SARS-CoV-2 virus, coupled with its potentially lethal outcome, provoked a profound global economic and social crisis. The urgency of finding suitable pharmacological tools to tame the pandemic shed light on the ever-increasing importance of computer simulations in rationalizing and speeding up the design of new drugs, further stressing the need for developing quick and reliable methods to identify novel active molecules and characterize their mechanism of action. In the present work, we aim at providing the reader with a general overview of the COVID-19 pandemic, discussing the hallmarks in its management, from the initial attempts at drug repurposing to the commercialization of Paxlovid, the first orally available COVID-19 drug. Furthermore, we analyze and discuss the role of computer-aided drug discovery (CADD) techniques, especially those that fall in the structure-based drug design (SBDD) category, in facing present and future pandemics, by showcasing several successful examples of drug discovery campaigns where commonly used methods such as docking and molecular dynamics have been employed in the rational design of effective therapeutic entities against COVID-19.

Mechanistic Insight into the Inhibition of Choline Acetyltransferase by Proton Pump Inhibitors

Various pharmacoepidemiological investigational studies have indicated that Proton Pump Inhibitors (PPIs) may increase the likelihood of developing Alzheimer's disease (AD) and non-AD related dementias. Previously, we have reported the inhibition of the acetylcholine biosynthesizing enzyme choline acetyltransferase (ChAT) by PPIs, for which omeprazole, lansoprazole, and pantoprazole exhibited IC₅₀ values of 0.1, 1.5, and 5.3 μM, respectively. In this study we utilize a battery of computational tools to perceive a mechanistic insight into the molecular interaction of PPIs with the ChAT binding pocket that may further help in designing novel ChAT ligands. Various in-silico tools make it possible for us to elucidate the binding interaction, conformational stability, and dynamics of the protein-ligand complexes within a 200 ns time frame. Further, the binding free energies for the PPI-ChAT complexes were explored. The results suggest that the PPIs exhibit equal or higher binding affinity toward the ChAT catalytic tunnel and are stable throughout the simulated time and that the pyridine ring of the PPIs interacts primarily with the catalytic residue His₃₂₄. A free energy landscape analysis showed that the folding process was linear, and the residue interaction network analysis can provide insight into the roles of various amino acid residues in stabilization of the PPIs in the ChAT binding pocket. As a major factor for the onset of Alzheimer's disease is linked to cholinergic dysfunction, our previous and the present findings give clear insight into the PPI interaction with ChAT. The scaffold can be further simplified to develop novel ChAT ligands, which can also be used as ChAT tracer probes for the diagnosis of cholinergic dysfunction and to initiate timely therapeutic interventions to prevent or delay the progression of AD.

Thermal Titration Molecular Dynamics (TTMD): Not Your Usual Post-Docking Refinement

Molecular docking is one of the most widely used computational approaches in the field of rational drug design, thanks to its favorable balance between the rapidity of execution and the accuracy of provided results. Although very efficient in exploring the conformational degrees of freedom available to the ligand, docking programs can sometimes suffer from inaccurate scoring and ranking of generated poses. To address this issue, several post-docking filters and refinement protocols have been proposed throughout the years, including pharmacophore models and molecular dynamics simulations. In this work, we present the first application of Thermal Titration Molecular Dynamics (TTMD), a recently developed method for the qualitative estimation of protein-ligand unbinding kinetics, to the refinement of docking results. TTMD evaluates the conservation of the native binding mode throughout a series of molecular dynamics simulations performed at progressively increasing temperatures with a scoring function based on protein-ligand interaction fingerprints. The protocol was successfully applied to retrieve the native-like binding pose among a set of decoy poses of drug-like ligands generated on four different pharmaceutically relevant biological targets, including casein kinase 1δ, casein kinase 2, pyruvate dehydrogenase kinase 2, and SARS-CoV-2 main protease.

Trends and hotspots for European Journal of Medicinal Chemistry: A bibliometric study

European Journal of Medicinal Chemistry (EJMC) has been around for a long time and has gained broad interest from the various individuals working in the field. However, there is no bibliometric analysis on the publications of EJMC to thoroughly assess the scientific output and current status systematically. Therefore, the study was conducted to analyze the various publications of EJMC from 1987 to 2022 to improve their quality. A total of 13,386 papers were retrieved, with the number of publications increasing yearly. Based on the multiple indicators of bibliometrics, the highest impact countries, institutions, authors and representative literature were identified, and visualization networks were constructed using VOSviewer. Keyword co-occurrence analysis reveals a gradual shift from phenotypic drug discovery to target-based drug discovery in the EJMC theme change. Moreover, further discussion of the keyword clustering results is provided to support researchers in defining the scope of their research topics and planning their research directions. At this stage, there is a greater focus on developing antitumor and oxidative stress-related drugs than on the earlier anti-infective activities. In future studies, the main research directions are tumor multidrug resistance, oxidative stress, and dual inhibitors.

Structural Basis for Agonistic Activity and Selectivity toward Melatonin Receptors hMT1 and hMT2

Glaucoma, a major ocular neuropathy originating from a progressive degeneration of retinal ganglion cells, is often associated with increased intraocular pressure (IOP). Daily IOP fluctuations are physiologically influenced by the antioxidant and signaling activities of melatonin. This endogenous modulator has limited employment in treating altered IOP disorders due to its low stability and bioavailability. The search for low-toxic compounds as potential melatonin agonists with higher stability and bioavailability than melatonin itself could start only from knowing the molecular basis of melatonergic activity. Thus, using a computational approach, we studied the melatonin binding toward its natural macromolecular targets, namely melatonin receptors 1 (MT1) and 2 (MT2), both involved in IOP signaling regulation. Besides, agomelatine, a melatonin-derivative agonist and, at the same time, an atypical antidepressant, was also included in the study due to its powerful IOP-lowering effects. For both ligands, we evaluated both stability and ligand positioning inside the orthosteric site of MTs, mapping the main molecular interactions responsible for receptor activation. Affinity values in terms of free binding energy (ΔG_bind) were calculated for the selected poses of the chosen compounds after stabilization through a dynamic molecular docking protocol. The results were compared with experimental in vivo effects, showing a higher potency and more durable effect for agomelatine with respect to melatonin, which could be ascribed both to its higher affinity for hMT2 and to its additional activity as an antagonist for the serotonin receptor 5-HT2c, in agreement with the in silico results.

Structural and functional characterisation of HepTH1-5 peptide as a potential hepcidin replacement

Hepcidin is a principal regulator of iron homeostasis and its dysregulation has been recognised as a causative factor in cancers and iron disorders. The strategy of manipulating the presence of hepcidin peptide has been used for cancer treatment. However, this has demonstrated poor efficiency and has been short-lived in patients. Many studies reported using minihepcidin therapy as an alternative way to treat hepcidin dysregulation, but this was only applied to non-cancer patients. Highly conserved fish hepcidin protein, HepTH1-5, was investigated to determine its potential use in developing a hepcidin replacement for human hepcidin (Hepc25) and as a therapeutic agent by targeting the tumour suppressor protein, p53, through structure-function analysis. The authors found that HepTH1-5 is stably bound to ferroportin, compared to Hepc25, by triggering the ferroportin internalisation via Lys42 and Lys270 ubiquitination, in a similar manner to the Hepc25 activity. Moreover, the residues Ile24 and Gly24, along with copper and zinc ligands, interacted with similar residues, Lys24 and Asp1 of Hepc25, respectively, showing that those molecules are crucial to the hepcidin replacement strategy. HepTH1-5 interacts with p53 and activates its function through phosphorylation. This finding shows that HepTH1-5 might be involved in the apoptosis signalling pathway upon a DNA damage response. This study will be very helpful for understanding the mechanism of the hepcidin replacement and providing insights into the HepTH1-5 peptide as a new target for hepcidin and cancer therapeutics.Communicated by Ramaswamy H. Sarma.

Evaluating the Antimicrobial and Anti-Hemolytic Activity of Synthesized Pseudopeptide against Leptospiral Species: In Silico and In Vitro Approach

Bacterial infections are one of the leading causes of morbidity, mortality, and healthcare complications in patients. Leptospirosis is found to be the most prevalent, re-emergent, and neglected tropical zoonotic disease worldwide. The adaptation to various environmental conditions has made Leptospira acquire a large genome (~4.6 Mb) and a complex outer membrane, making it unique among bacteria that mimic the symptoms of jaundice and hemorrhage. Sph2 is another important virulence factor that enhances hemolytic sphingomyelinase-capable of moving inside mitochondria-which increases the ROS level and decreases the mitochondrial membrane potential, thereby leading to cell apoptosis. In the present study, 25 suspected bovine serum samples were subjected to the Microscopic Agglutination Test (MAT) across the Mysuru region. Different samples, such as urine, serum, and aborted materials from the confirmed MAT-positive animals, were used for isolation and genomic detection by conventional PCR targeting virulence gene, Lipl32, using specific primers. Further, in vitro and in silico studies were performed on isolated cultures to assess the anti-leptospiral, anti-hemolytic, and sphingomyelinase enzyme inhibition using novel pseudopeptides. The microdilution technique (MDT) and dark field microscope (DFM) assays revealed that at a concentration of 62.5 μg/mL, the pseudopeptide inhibited 100% of the growth of Leptospira spp., suggesting its efficiency in the treatment of leptospirosis. The flow cytometry analyses show the potency of the pseudopeptide against sphingomyelinase enzymes using human umbilical vein endothelial cells (HUVECs). Thus, the present study demonstrated the efficacy of the pseudopeptide in the inhibition of the growth of Leptospira, and therefore, this can be used as an alternative drug for the treatment of leptospirosis.