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

Accurate prediction of dynamic protein-ligand binding using P-score ranking

Protein-ligand binding prediction typically relies on docking methodologies and associated scoring functions to propose the binding mode of a ligand in a biological target. Significant challenges are associated with this approach, including the flexibility of the protein-ligand system, solvent-mediated interactions, and associated entropy changes. In addition, scoring functions are only weakly accurate due to the short time required for calculating enthalpic and entropic binding interactions. The workflow described here attempts to address these limitations by combining supervised molecular dynamics with dynamical averaging quantum mechanics fragment molecular orbital. This combination significantly increased the ability to predict the experimental binding structure of protein-ligand complexes independent from the starting position of the ligands or the binding site conformation. We found that the predictive power could be enhanced by combining the residence time and interaction energies as descriptors in a novel scoring function named the P-score. This is illustrated using six different protein-ligand targets as case studies.

Protective efficacy of nafronyl in diabetic retinopathy through targeted inhibition of key enzymes

Diabetic retinopathy is governed by abnormal apoptosis, increased capillary pressure, and other linked pathology that needs an efficient treatment by multitargeted approaches. Thus, the current study aimed to explore the potential of inhibition of targeted enzymes (DPP4, ACE-2, and aldose reductase) and free radical scavenging capabilities of selected compounds (nafronyl or naftidrofuryl) through in silico and in vivo investigations. Significant binding energies were observed in complexes of aldolase reductase, angiotensin type 1 receptor, and DPP4 against the nafronyl and sitagliptin more than -7.5 kcal/mol. Further validation of free energy was confirmed by calculations of molecular mechanics Poisson-Boltzmann surface area (MMPBSA), and configurational stabilities examined by PCA (principal component analysis). Additionally, drug-likeness was examined by the Swiss ADME web tool, which showed significant findings. Consequently, in vivo experimentations showed significant inflammation and alterations in retinal layers of inner plexiform (inner limiting membrane, nerve fibers, and ganglionic cells), inner nuclear layer (bipolar cells and horizontal cells), and photoreceptors cells. Whereas the treatments (nafronyl and sitagliptin) caused significant improvements in the histoarchitecture of the retina. Additionally, the HOMA indices (IR-insulin resistance, sensitivity, and β cells functioning) and levels of free radicals were significantly altered in the diabetic control group in comparison to intact control. Nafronyl administration showed significant ameliorations in HOMA indices as well as antioxidant levels. Based on the results, it can be concluded that nafronyl efficiently interacts with target enzymes, which may result in potent inhibition and ameliorations in retinal histology as well as glucose homeostasis and antioxidants.

Accurate and Efficient Conformer Sampling of Cyclic Drug-Like Molecules with Inverse Kinematics

Identification of all of the influential conformers of biomolecules is a crucial step in many tasks of computational biochemistry. Specifically, molecular docking, a key component of in silico drug development, requires a comprehensive set of conformations for potential candidates in order to generate the optimal ligand-receptor poses and, ultimately, find the best drug candidates. However, the presence of flexible cycles in a molecule complicates the initial search for conformers since exhaustive sampling algorithms via torsional random and systematic searches become very inefficient. The devised inverse-kinematics-based Monte Carlo with refinement (MCR) algorithm identifies independently rotatable dihedral angles in (poly)cyclic molecules and uses them to perform global conformational sampling, outperforming popular alternatives (MacroModel, CREST, and RDKit) in terms of speed and diversity of the resulting conformer ensembles. Moreover, MCR quickly and accurately recovers naturally occurring macrocycle conformations for most of the considered molecules.

Exploring the mechanism of action of spirooxindoles as a class of CDK2 inhibitors: a structure-based computational approach

Cyclin-dependent kinase 2 (CDK2) regulates cell cycle checkpoints in the synthesis and mitosis phases and plays a pivotal role in cancerous cell proliferation. The activation of CDK2, influenced by various protein signaling pathways, initiates the phosphorylation process. Due to its crucial role in carcinogenesis, CDK2 is a druggable hotspot target to suppress cancer cell proliferation. In this context, several studies have identified spirooxindoles as an effective class of CDK2 inhibitors. In the present study, three spirooxindoles (SOI1, SOI2, and SOI3) were studied to understand their inhibitory mechanism against CDK2 through a structure-based approach. Molecular docking and molecular dynamics (MD) simulations were performed to explore their interactions with CDK2 at the molecular level. The calculated binding free energy for the spirooxindole-based CDK2 inhibitors aligned well with experimental results regarding CDK2 inhibition. Energy decomposition (ED) analysis identified key binding residues, including I10, G11, T14, R36, F82, K89, L134, P155, T158, Y159, and T160, in the CDK2 active site and T-loop phosphorylation. Molecular mechanics (MM) energy was identified as the primary contributor to stabilizing inhibitor binding in the CDK2 protein structure. Furthermore, the analysis of binding affinity revealed that the inhibitor SOI1 binds more strongly to CDK2 compared to the other inhibitors under investigation. It demonstrated a robust interaction with the crucial residue T160 in the T-loop phosphorylation site, responsible for kinase activation. These insights into the inhibitory mechanism are anticipated to contribute to the development of potential CDK2 inhibitors using the spirooxindole scaffold.

Benchmarking compound activity prediction for real-world drug discovery applications

Identifying active compounds for target proteins is fundamental in early drug discovery. Recently, data-driven computational methods have demonstrated promising potential in predicting compound activities. However, there lacks a well-designed benchmark to comprehensively evaluate these methods from a practical perspective. To fill this gap, we propose a Compound Activity benchmark for Real-world Applications (CARA). Through carefully distinguishing assay types, designing train-test splitting schemes and selecting evaluation metrics, CARA can consider the biased distribution of current real-world compound activity data and avoid overestimation of model performances. We observed that although current models can make successful predictions for certain proportions of assays, their performances varied across different assays. In addition, evaluation of several few-shot training strategies demonstrated different performances related to task types. Overall, we provide a high-quality dataset for developing and evaluating compound activity prediction models, and the analyses in this work may inspire better applications of data-driven models in drug discovery.

Potential anti-liver cancer targets and mechanisms of kaempferitrin based on network pharmacology, molecular docking and experimental verification

AIM

Kaempferitrin is an active component in Chenopodium ambrosioides, showing medicinal functions against liver cancer. This study aimed to identify the potential targets and pathways of kaempferitrin against liver cancer using network pharmacology and molecular docking, and verify the essential hub targets and pathway in mice model of SMMC-7721 cells xenografted tumors and SMMC-7721 cells.

METHODS

Kaempferitrin therapeutical targets were obtained by searching SwissTargetPrediction, PharmMapper, STITCH, DrugBank, and TTD databases. Liver cancer specific genes were obtained by searching GeneCards, DrugBank, TTD, OMIM, and DisGeNET databases. PPI network of "kaempferitrin-targets-liver cancer" was constructed to screen the hub targets. GO, KEGG pathway and MCODE clustering analyses were performed to identify possible enrichment of genes with specific biological subjects. Molecular docking and molecular dynamics simulation were employed to determine the docking pose, potential and stability of kaempferitrin with hub targets. The potential anti-liver cancer mechanisms of kaempferitrin, as predicted by network pharmacology analyses, were verified by in vitro and in vivo experiments.

RESULTS

228 kaempferitrin targets and 2186 liver cancer specific targets were identified, of which 50 targets were overlapped. 8 hub targets were identified through network topology analysis, and only SIRT1 and TP53 had a potent binding activity with kaempferitrin as indicated by molecular docking and molecular dynamics simulation. MCODE clustering analysis revealed the most significant functional module of PPI network including SIRT1 and TP53 was mainly related to cell apoptosis. GO and KEGG enrichment analyses suggested that kaempferitrin exerted therapeutic effects on liver cancer possibly by promoting apoptosis via p21/Bcl-2/Caspase 3 signaling pathway, which were confirmed by in vivo and in vitro experiments, such as HE staining of tumor tissues, CCK-8, qRT-PCR and Western blot.

CONCLUSION

This study provided not only insight into how kaempferitrin could act against liver cancer by identifying hub targets and their associated signaling pathways, but also experimental evidence for the clinical use of kaempferitrin in liver cancer treatment.

Nature-inspired substituted 3-(imidazol-2-yl) morpholines targeting human topoisomerase IIα: Dynophore-derived discovery

The molecular nanomachine, human DNA topoisomerase IIα, plays a crucial role in replication, transcription, and recombination by catalyzing topological changes in the DNA, rendering it an optimal target for cancer chemotherapy. Current clinical topoisomerase II poisons often cause secondary tumors as side effects due to the accumulation of double-strand breaks in the DNA, spurring the development of catalytic inhibitors. Here, we used a dynamic pharmacophore approach to develop catalytic inhibitors targeting the ATP binding site of human DNA topoisomerase IIα. Our screening of a library of nature-inspired compounds led to the discovery of a class of 3-(imidazol-2-yl) morpholines as potent catalytic inhibitors that bind to the ATPase domain. Further experimental and computational studies identified hit compound 17, which exhibited selectivity against the human DNA topoisomerase IIα versus human protein kinases, cytotoxicity against several human cancer cells, and did not induce DNA double-strand breaks, making it distinct from clinical topoisomerase II poisons. This study integrates an innovative natural product-inspired chemistry and successful implementation of a molecular design strategy that incorporates a dynamic component of ligand-target molecular recognition, with comprehensive experimental characterization leading to hit compounds with potential impact on the development of more efficient chemotherapies.

Exploring the potential of P-glycoprotein inhibitors in the targeted delivery of anti-cancer drugs: A comprehensive review

Due to the high prevalence of cancer, progress in the management of cancer is the need of the hour. Most cancer patients develop chemotherapeutic drug resistance, and many remain insidious due to overexpression of Multidrug Resistance Protein 1 (MDR1), also known as Permeability-glycoprotein (P-gp) or ABCB1 transporter (ATP-binding cassette subfamily B member 1). P-gp, a transmembrane protein that protects vital organs from outside chemicals, expels medications from malignant cells. The blood-brain barrier (BBB), gastrointestinal tract (GIT), kidneys, liver, pancreas, and cancer cells overexpress P-gp on their apical surfaces, making treatment inefficient and resistant. Compounds that compete with anticancer medicines for transportation or directly inhibit P-gp may overcome biological barriers. Developing nanotechnology-based formulations may help overcome P-gp-mediated efflux and improve bioavailability and cell chemotherapeutic agent accumulation. Nanocarriers transport pharmaceuticals via receptor-mediated endocytosis, unlike passive diffusion, which bypasses ABCB1. Anticancer drugs and P-gp inhibitors in nanocarriers may synergistically increase drug accumulation and chemotherapeutic agent toxicity. The projection of desirable binding and effect may be procured initially by molecular docking of the inhibitor with P-gp, enabling the reduction of preliminary trials in formulation development. Here, P-gp-mediated efflux and several possible outcomes to overcome the problems associated with currently prevalent cancer treatments are highlighted.

Discovery of a New Class of 1-(4-Sulfamoylbenzoyl)piperidine-4-carboxamides as Human Carbonic Anhydrase Inhibitors

A series of 1-(4-sulfamoylbenzoyl)piperidine-4-carboxamides deriving from substituted piperazines/benzylamines was designed, synthesized, and tested on human carbonic anhydrase (hCA). The inhibitory activity of the new sulfonamides was analyzed using acetazolamide (AAZ) as a standard inhibitor against hCA I, II, IX, and XII. Several sulfonamides showed both inhibitory activity at low nanomolar concentrations and selectivity against the cytosolic hCA II isoform, and the same trend was observed on the tumor-associated hCA IX and XII. The benzenesulfonamido carboxamides 11 and 15 were the most potent of the piperazino- and benzylamino-based series, respectively. Docking and molecular dynamics studies related the high selectivity of compound 11 toward the tumor-associated hCA isoforms to its capability to participate in favorable interactions within hCA IX and hCA XII active sites, whereas no such interactions were detected within both hCA I and hCA II isoforms.

Machine Learning Integrating Protein Structure, Sequence, and Dynamics to Predict the Enzyme Activity of Bovine Enterokinase Variants

Despite recent advances in computational protein science, the dynamic behavior of proteins, which directly governs their biological activity, cannot be gleaned from sequence information alone. To overcome this challenge, we propose a framework that integrates the peptide sequence, protein structure, and protein dynamics descriptors into machine learning algorithms to enhance their predictive capabilities and achieve improved prediction of the protein variant function. The resulting machine learning pipeline integrates traditional sequence and structure information with molecular dynamics simulation data to predict the effects of multiple point mutations on the fold improvement of the activity of bovine enterokinase variants. This study highlights how the combination of structural and dynamic data can provide predictive insights into protein functionality and address protein engineering challenges in industrial contexts.

Docking and Molecular Dynamics Simulation Revealed the Potential Inhibitory Activity of Amygdalin in Triple-Negative Breast Cancer Therapeutics Targeting the BRCT Domain of BARD1 Receptor

Triple-negative breast cancer (TNBC), is diagnosed as the most lethal molecular subtype of breast cancer (BC) preceded by an extremely poor prognosis. For enabling effective TNBC therapy, the identification of novel druggable biomarkers is an earnest need. Multigene paneling and genomewide association studies identify multiple genes with high-to-moderate penetrance in TNBC. Modern computer-aided drug designing techniques, thus aim to design more cost-effective natural small molecule inhibitors for TNBC prevention and diagnosis. Here Amygdalin, a natural glycosidic inhibitor is docked and simulated against three such high-to-moderate penetrance genes identified in TNBC, BARD1, RAD51, and PALB2. The preliminary result of the analysis, reports a highest, intermediate, and least binding energy score of - 6.69 kcal/mol, - 5.09 kcal/mol, and - 4.89 kcal/mol in BARD1, RAD51, and PALB2, respectively. The best-docked protein-ligand complex (BARD1-Amygdalin) was then simulated and compared with an approved drug for TNBC treatment, Olaparib. A comparable binding energy score of - 8.53 kcal/mol was obtained by docking olaparib with BARD1. A 100 ns MD simulation revealed, Amygdalin forms more H-bonds, providing more stable and compact protein-ligand complex with BARD1 than compared to Olaparib. The result was also supported by calculation of solvent accessible surface area and analysis of radius of gyration. Thus, our findings suggest that role of Amygdalin can further be studied in details for TNBC therapeutics, which was found to target the BRCT domain of the BARD1 receptor in stable manner. Please check and confirm that the authors and their respective affiliations have been correctly identified and amend if necessary. Name and affiliations are correctly identified.

Metabolite Profiling of Colvillea racemosa via UPLC-ESI-QTOF-MS Analysis in Correlation to the In Vitro Antioxidant and Cytotoxic Potential against A549 Non-Small Cell Lung Cancer Cell Line

In this study, flower and leaf extracts of Colvillea racemosa were considered a source of bioactive compounds. In this context, the objective of the study focused on investigating the anticancer potential as well as the phytochemical composition of both extracts. The extracts were analyzed by UPLC-ESI-QTOF-MS, and the bioactivity was tested using in vitro antioxidant assays (FRAP, DPPH, and ABTS) in addition to cytotoxic assays on non-small cell lung cancer cell line (A549). Our results clearly indicated the potent radical scavenging capacity of both extracts. Importantly, the flower extract exhibited a greater antioxidant capacity than the leaf extract. In terms of cytotoxic activity, leaf and flower extracts significantly inhibited cell viability with IC50 values of 17.0 and 17.2 µg/mL, respectively. The phytochemical characterization enabled the putative annotation of 42 metabolites, such as saccharides, phenolic acids, flavonoids, amino acids, and fatty acids. Among them, the flavonoid C-glycosides stand out due to their high relative abundance and previous reports on their anticancer bioactivity. For a better understanding of the bioactive mechanisms, four flavonoids (vitexin, kaempferol-3-O-rutinoside, luteolin, and isoorientin) were selected for molecular docking on hallmark protein targets in lung cancer as represented by γ-PI3K, EGFR, and CDK2 through in-silico studies. In these models, kaempferol-3-O-rutinoside and vitexin had the highest binding scores on γ-PI3K and CDK2, followed by isoorientin, so they could be highly responsible for the bioactive properties of C. racemosa extracts.

Design, synthesis and anticholinergic properties of novel α-benzyl dopamine, tyramine, and phenethylamine derivatives

Due to the important biological properties of dopamine, phenethylamine, and tyramine derivatives in the central nervous system, herein the synthesis of novel α-benzyl dopamine, phenethylamine, and tyramine derivatives is described. The title compounds were synthesized starting from 3-phenylpropanoic acids and methoxybenzenes in six or seven steps. Firstly, 3-(2,3-dimethoxyphenyl)propanoic acid (11) and 3-(3,4-dimethoxyphenyl)propanoic acid (12) were selectively brominated with N-bromosuccinimide (NBS). The Friedel-Crafts acylation of methoxylated benzenes with these brominated acids or commercially available 3-phenylpropanoic acid in polyphosphoric acid gave the desired dihydrochalcones. α-Carboxylation of dihydrochalcones, reduction of benzylic carbonyl groups, hydrolysis of esters to acid derivatives, and the Curtius rearrangement reaction of acids followed by in situ synthesis of carbamates from alkyl isocyanates and hydrogenolysis of the carbamates afforded the title compounds in good total yields. Alzheimer's disease (AD) and Parkinson's disease (PD) are chronic neurodegenerative diseases that become serious over time. However, the exact pathophysiology of both diseases has not been revealed yet. There have been many different approaches to the treatment of patients for many years, especially studies on the cholinergic system cover a wide area. Within the scope of this study, the inhibition effects of dopamine-derived carbamates and amine salts on the cholinergic enzymes AChE and BChE were examined. Dopamine-derived carbamate 24a-i showed inhibition in the micro-nanomolar range; compound 24d showed a Ki value of 26.79 nM against AChE and 3.33 nM against BChE, while another molecule, 24i, showed a Ki range of 27.24 nM and 0.92 nM against AChE and BChE, respectively. AChE and BChE were effectively inhibited by dopamine-derived amine salts 25j-s, with Ki values in the range of 17.70 to 468.57 µM and 0.76-211.23 µM, respectively. Additionally, 24c, 24e and 25m were determined to be 60, 276 and 90 times more selective against BChE than AChE, respectively.

The role of Aedes aegypti in inducing/aggravating IgE-mediated allergic airway disease: extensive computational studies for identification of allergenic proteins

Respiratory allergies have become a major public health concern and affect one-third of the world's population. Several factors like environmental changes, industrialization, and immunologic interactions are reported to contribute to allergic respiratory diseases. Immunological reactions because of mosquito bite (allergic proteins) have been reported to have a high contribution to IgE-mediated allergic airway disease but they are largely ignored. In this study, we aim to predict the potential allergens (proteins) from Aedes aegypti that might play a role in the reactions of IgE-mediated allergic airway diseases. The allergens are identified from an extensive literature search and the 3D structures were prepared using the SwissDock server. Computational studies were performed to identify the potential allergens that might be responsible for IgE-mediated allergies. Our docking and molecular dynamics (MD) simulation results suggest that ADE-3, an allergen from Aedes aegypti, has the highest docking score and is predicted to be responsible for IgE-mediated allergic reaction(s). Overall, this study highlights the importance of immunoinformatics, and the obtained information can be used for designing prophylactic peptide vaccine candidates and inhibitors for controlling IgE-mediated inflammations.Communicated by Ramaswamy H. Sarma.

Machine learning driven web-based app platform for the discovery of monoamine oxidase B inhibitors

Monoamine oxidases (MAOs), specifically MAO-A and MAO-B, play important roles in the breakdown of monoamine neurotransmitters. Therefore, MAO inhibitors are crucial for treating various neurodegenerative disorders, including Parkinson's disease (PD), Alzheimer's disease (AD), and amyotrophic lateral sclerosis (ALS). In this study, we developed a novel cheminformatics pipeline by generating three diverse molecular feature-based machine learning-assisted quantitative structural activity relationship (ML-QSAR) models concerning MAO-B inhibition. PubChem fingerprints, substructure fingerprints, and one-dimensional (1D) and two-dimensional (2D) molecular descriptors were implemented to unravel the structural insights responsible for decoding the origin of MAO-B inhibition in 249 non-reductant molecules. Based on a random forest ML algorithm, the final PubChem fingerprint, substructure fingerprint, and 1D and 2D molecular descriptor prediction models demonstrated significant robustness, with correlation coefficients of 0.9863, 0.9796, and 0.9852, respectively. The significant features of each predictive model responsible for MAO-B inhibition were extracted using a comprehensive variance importance plot (VIP) and correlation matrix analysis. The final predictive models were further developed as a web application, MAO-B-pred ( https://mao-b-pred.streamlit.app/ ), to allow users to predict the bioactivity of molecules against MAO-B. Molecular docking and dynamics studies were conducted to gain insight into the atomic-level molecular interactions between the ligand-receptor complexes. These findings were compared with the structural features obtained from the ML-QSAR models, which supported the mechanistic understanding of the binding phenomena. The presented models have the potential to serve as tools for identifying crucial molecular characteristics for the rational design of MAO-B target inhibitors, which may be used to develop effective drugs for neurodegenerative disorders.

Binomial Uncertainty in Molecular Dynamics-Based Reactions Analysis

Molecular Dynamics-based reaction analysis is an indispensable tool for studying processes defying the transition-state theory (TST), where the product ratios do not follow energies of transition states. The main class of such processes is ambimodal reactions, which have a post-transition-state bifurcation, so that several products form via a single transition state. Multiple runs of molecular dynamics allow one to sample the space of possibilities and ultimately predict the product ratio without relying on TST; however, no techniques for estimating the reliability of the prediction were proposed so far. Here we show that dynamics runs follow the same rules as die rolls, which paves a simple way for estimating their uncertainty and, accordingly, the number of runs necessary to achieve the required accuracy. Remarkably, we find that the majority of such studies carried out in the last 5 years use far too few runs, so that the product ratios predicted in them can be off by >50% in more than 50% of cases.

Unveiling the Antiviral Efficacy of Forskolin: A Multifaceted In Vitro and In Silico Approach

Coleus forskohlii (Willd.) Briq. is a medicinal herb of the Lamiaceae family. It is native to India and widely present in the tropical and sub-tropical regions of Egypt, China, Ethiopia, and Pakistan. The roots of C. forskohlii are edible, rich with pharmaceutically bioactive compounds, and traditionally reported to treat a variety of diseases, including inflammation, respiratory disorders, obesity, and viral ailments. Notably, the emergence of viral diseases is expected to quickly spread; consequently, these data impose a need for various approaches to develop broad active therapeutics for utilization in the management of future viral infectious outbreaks. In this study, the naturally occurring labdane diterpenoid derivative, Forskolin, was obtained from Coleus forskohlii. Additionally, we evaluated the antiviral potential of Forskolin towards three viruses, namely the herpes simplex viruses 1 and 2 (HSV-1 and HSV-2), hepatitis A virus (HAV), and coxsackievirus B4 (COX-B4). We observed that Forskolin displayed antiviral activity against HAV, COX-B4, HSV-1, and HSV-2 with IC50 values of 62.9, 73.1, 99.0, and 106.0 μg/mL, respectively. Furthermore, we explored the Forskolin's potential antiviral target using PharmMapper, a pharmacophore-based virtual screening platform. Forskolin's modeled structure was analyzed to identify potential protein targets linked to its antiviral activity, with results ranked based on Fit scores. Cathepsin L (PDB ID: 3BC3) emerged as a top-scoring hit, prompting further exploration through molecular docking and MD simulations. Our analysis revealed that Forskolin's binding mode within Cathepsin L's active site, characterized by stable hydrogen bonding and hydrophobic interactions, mirrors that of a co-crystallized inhibitor. These findings, supported by consistent RMSD profiles and similar binding free energies, suggest Forskolin's potential in inhibiting Cathepsin L, highlighting its promise as an antiviral agent.

In silico drug repurposing by combining machine learning classification model and molecular dynamics to identify a potential OGT inhibitor

O-linked N-acetylglucosamine (O-GlcNAc) is a unique intracellular post-translational glycosylation at the hydroxyl group of serine or threonine residues in nuclear, cytoplasmic and mitochondrial proteins. The enzyme O-GlcNAc transferase (OGT) is responsible for adding GlcNAc, and anomalies in this process can lead to the development of diseases associated with metabolic imbalance, such as diabetes and cancer. Repurposing approved drugs can be an attractive tool to discover new targets reducing time and costs in the drug design. This work focuses on drug repurposing to OGT targets by virtual screening of FDA-approved drugs through consensus machine learning (ML) models from an imbalanced dataset. We developed a classification model using docking scores and ligand descriptors. The SMOTE approach to resampling the dataset showed excellent statistical values in five of the seven ML algorithms to create models from the training set, with sensitivity, specificity and accuracy over 90% and Matthew's correlation coefficient greater than 0.8. The pose analysis obtained by molecular docking showed only H-bond interaction with the OGT C-Cat domain. The molecular dynamics simulation showed the lack of H-bond interactions with the C- and N-catalytic domains allowed the drug to exit the binding site. Our results showed that the non-steroidal anti-inflammatory celecoxib could be a potentially OGT inhibitor.

Identification of potentially high drug-like VEGFR2/c-Met dual-target type II kinase inhibitors with symmetric skeletons based on structural screening

Vascular endothelial growth factor receptor 2 (VEGFR2) and c-Mesenchymal epithelial transition factor (c-Met) are tyrosine kinase receptors associated with the occurrence of malignant tumors. Studies have shown that inhibition of VEGFR2 promotes a feedback increase in c-Met, a mechanism linked to the emergence of resistance to VEGFR2 inhibitors. Therefore, treatment targeting both VEGFR2 and c-Met will have better application prospects. In this study, hierarchical virtual screening was performed on ZINC15, Molport and Mcule-ULTIMATE databases to identify potential VEGFR2/c-Met dual inhibitors. Firstly, the best pharmacophore model for each target was used to cross-screen the three databases, and the compounds that could match the two pharmacophore models were then retained based on the Fit Value of the respective crystal ligands. Compounds ZINC, MOL, and MLB named after their database sources were retained by binding pattern analysis and docking assessment. ADMET predictions indicated that ZINC had significantly higher oral bioavailability compared to the approved drug cabozantinib. This is likely due to ZINC's unique symmetrical backbone with less structure complexity, which may reduce the occurrence of adverse effects. Molecular dynamics simulations and binding free energy analysis showed that all three hit compounds were able to stably bind at the active site, but only ZINC could form high occupancy of hydrogen bonds with both VEGFR2 and c-Met, and also only ZINC had a higher binding free energy than crystal ligands, suggesting that ZINC was the most likely potential VEGFR2/c-Met dual-target inhibitor. This finding provides a promising starting point for the development of VEGFR2/c-Met dual-target inhibitors.Communicated by Ramaswamy H. Sarma.

Tunnel engineering of gas-converting enzymes for inhibitor retardation and substrate acceleration

Carbon monoxide dehydrogenase (CODH), formate dehydrogenase (FDH), hydrogenase (H2ase), and nitrogenase (N2ase) are crucial enzymatic catalysts that facilitate the conversion of industrially significant gases such as CO, CO2, H2, and N2. The tunnels in the gas-converting enzymes serve as conduits for these low molecular weight gases to access deeply buried catalytic sites. The identification of the substrate tunnels is imperative for comprehending the substrate selectivity mechanism underlying these gas-converting enzymes. This knowledge also holds substantial value for industrial applications, particularly in addressing the challenges associated with separation and utilization of byproduct gases. In this comprehensive review, we delve into the emerging field of tunnel engineering, presenting a range of approaches and analyses. Additionally, we propose methodologies for the systematic design of enzymes, with the ultimate goal of advancing protein engineering strategies.

Virtual Screening of Peptide Libraries: The Search for Peptide-Based Therapeutics Using Computational Tools

Over the last few decades, we have witnessed growing interest from both academic and industrial laboratories in peptides as possible therapeutics. Bioactive peptides have a high potential to treat various diseases with specificity and biological safety. Compared to small molecules, peptides represent better candidates as inhibitors (or general modulators) of key protein-protein interactions. In fact, undruggable proteins containing large and smooth surfaces can be more easily targeted with the conformational plasticity of peptides. The discovery of bioactive peptides, working against disease-relevant protein targets, generally requires the high-throughput screening of large libraries, and in silico approaches are highly exploited for their low-cost incidence and efficiency. The present review reports on the potential challenges linked to the employment of peptides as therapeutics and describes computational approaches, mainly structure-based virtual screening (SBVS), to support the identification of novel peptides for therapeutic implementations. Cutting-edge SBVS strategies are reviewed along with examples of applications focused on diverse classes of bioactive peptides (i.e., anticancer, antimicrobial/antiviral peptides, peptides blocking amyloid fiber formation).

Glass Transition Temperatures and Thermal Conductivities of Polybutadiene Crosslinked with Randomly Distributed Sulfur Chains Using Molecular Dynamic Simulation

The thermal conductivities and glass transition temperatures of polybutadiene crosslinked with randomly distributed sulfur chains having different lengths from mono-sulfur (S1) to octa-sulfur (S8) were investigated. The thermal conductivities of the related models as a function of the heat flux autocorrelation function, applying an equilibrium molecular dynamic (EMD) simulation and the Green-Kubo method, were studied for a wide range of temperatures. The influence of the length of sulfur chains, degree of crosslinking, and molar mass of the crosslinker on the glass transition temperature and final values of thermal conductivities were studied. First, the degree of crosslinking is considered constant for the eight simulation models, from mono-sulfur (S1) to octa-sulfur (S8), while the molar mass of the sulfur is increases. The results show that the thermal conductivities of the crosslinked structure decrease with increasing temperature for each model. Moreover, by increasing the lengths of the sulfur chains and the molar weight of the crosslinker, thermal conductivity increases at a constant temperature. The MD simulation demonstrates that the glass transition temperature and density of the crosslinked structure enhance as the length of the sulfur chains and molar mass of the sulfur increase. Second, the molar weight of sulfur is considered constant in these eight models; therefore, the degree of crosslinking decreases with the increase in the lengths of the sulfur chains. The results show that the thermal conductivities of the crosslinked structure decrease with the increase in the temperature for each model. Moreover, by increasing the lengths of sulfur chains and thus decreasing the degree of crosslinking, the trend in changes in thermal conductivities are almost the same for all of these models, so thermal conductivity is constant for a specific temperature. In addition, the glass transition temperature and density of the crosslinked structure decrease.

Recent developments in molecular modeling tools and applications related to pharmaceutical and biomedical research

In modern pharmaceutical and biomedical research, molecular modeling represents a useful tool to explore processes and their mechanistic bases at the molecular level. Integrating experimental and virtual analysis is a fruitful approach to study ligand-receptor interaction in chemical, biochemical and biological environments. In these fields, molecular docking and molecular dynamics are considered privileged techniques for modeling (bio)macromolecules and related complexes. This review aims to present the current landscape of molecular modeling in pharmaceutical and biomedical research by examining selected representative applications published in the last years and highlighting current topics and trends of this field. Thus, a systematic compilation of all published literature has not been attempted herein. After a brief overview of the main theoretical and computational tools used to investigate mechanisms at molecular level, recent applications of molecular modeling in drug discovery, ligand binding and for studying protein conformation and function will be discussed. Furthermore, specific sections will be devoted to the application of molecular modeling for unravelling enantioselective mechanisms underlying the enantioseparation of chiral compounds of pharmaceutical and biomedical interest as well as for studying new forms of noncovalent interactivity identified in biochemical and biological environments. The general aim of this review is to provide the reader with a modern overview of the topic, highlighting advancements and outlooks as well as drawbacks and pitfalls still affecting the applicability of theoretical and computational methods in the field of pharmaceutical and biomedical research.

Inhibitory effects of selected cannabinoids against dipeptidyl peptidase IV, an enzyme linked to type 2 diabetes

Ethnopharmacological relevance

In recent times the decriminalisation of cannabis globally has increased its use as an alternative medication. Where it has been used in modern medicinal practises since the 1800s, there is limited scientific investigation to understand the biological activities of this plant.

Aim of the study

Dipeptidyl peptidase IV (DPP-IV) plays a key role in regulating glucose homeostasis, and inhibition of this enzyme has been used as a therapeutic approach to treat type 2 diabetes. However, some of the synthetic inhibitors for this enzyme available on the market may cause undesirable side effects. Therefore, it is important to identify new inhibitors of DPP-IV and to understand their interaction with this enzyme.

Methods

In this study, four cannabinoids (cannabidiol, cannabigerol, cannabinol and Δ9-tetrahydrocannabinol) were evaluated for their inhibitory effects against recombinant human DPP-IV and their potential inhibition mechanism was explored using both in vitro and in silico approaches.

Results

All four cannabinoids resulted in a dose-dependent response with IC50 values of between 4.0 and 6.9 μg/mL. Kinetic analysis revealed a mixed mode of inhibition. CD spectra indicated that binding of cannabinoids results in structural and conformational changes in the secondary structure of the enzyme. These findings were supported by molecular docking studies which revealed best docking scores at both active and allosteric sites for all tested inhibitors. Furthermore, molecular dynamics simulations showed that cannabinoids formed a stable complex with DPP-IV protein via hydrogen bonds at an allosteric site, suggesting that cannabinoids act by either inducing conformational changes or blocking the active site of the enzyme.

Conclusion

These results demonstrated that cannabinoids may modulate DPP-IV activity and thereby potentially assist in improving glycaemic regulation in type 2 diabetes.

Comprehending the intermolecular interaction of JAK inhibitor fedratinib with bovine serum albumin (BSA)/human alpha-1-acid glycoprotein (HAG): Multispectral methodologies and molecular simulation

The primary coverage of this paper is to investigate the molecular interaction of JAK2 inhibitor, fedratinib (FED) with BSA/HAG proteins through multispectral approaches and molecular docking as well as MD calculation. Arrival at a conclusion, the endogenous fluorescence of BSA/HAG protein was quenched separately in the form of static and mixed quenching. The FED-BSA and FED-HAG complexes with the stoichiometric ratio of 1:1 were formed in the interaction process. And, The Kb values of these complexes were of 104-105 M-1 and 105-106 M-1, respectively, representing that the FED-HAG complex exhibited a comparatively high affinity compared to the FED-BSA complex. It is confimed that FED inserted into the interface area between subdomain IIA and IIB of BSA (marked as site II') and the bucket-shaped hydrophobic cavity of HAG, respectively, resulting in the slight alteration in the secondary structure of BSA/HAG and the micro-environment round Tyr and Trp residues. The expetimental results also confirmed that van der Waals forces (VDW), hydrogen bonds and hydrophobic interaction played a dominant role in the formation of two stable complexes. The above experimental results were supplemented and verified through molecular docking and MD simulation. Meanwhile, the effects of common ions on affinity were explored. This study could shine a light on evaluating the pharmacological properties of the JAK inhibitor FED, understanding the distribution and operation of the drug in the body, and leading to the development of the creation of novel medication devise.

Natural sapogenins as potential inhibitors of aquaporins for targeted cancer therapy: computational insights into binding and inhibition mechanism

Aquaporins (AQPs) are membrane proteins that facilitate the transport of water and other small molecules across biological membranes. AQPs are involved in various physiological processes and pathological conditions, including cancer, making them as potential targets for anticancer therapy. However, the development of selective and effective inhibitors of AQPs remains a challenge. In this study, we explored the possibility of using natural sapogenins, a class of plant-derived aglycones of saponins with diverse biological activities, as potential inhibitors of AQPs. We performed molecular docking, dynamics simulation and binding energy calculation to investigate the binding and inhibition mechanism of 19 sapogenins against 13 AQPs (AQP0-AQP13) that are overexpressed in various cancers. Our results showed that out of 19 sapogenins, 8 (Diosgenin, Gitogenin, Tigogenin, Ruscogenin, Yamogenin, Hecogenin, Sarsasapogenin and Smilagenin) exhibited acceptable drug-like characteristics. These sapogenin also exhibited favourable binding affinities in the range of -7.6 to -13.4 kcal/mol, and interactions within the AQP binding sites. Furthermore, MD simulations provided insights into stability and dynamics of the sapogenin-AQP complexes. Most of the fluctuations in binding pocket were observed for AQP0-Gitogenin and AQP4-Diosgenin. However, remaining protein-ligand complex showed stable root mean square deviation (RMSD) plots, strong hydrogen bonding interactions, stable solvent-accessible surface area (SASA) values and minimum distance to the receptor. These observations suggest that natural sapogenin hold promise as novel inhibitors of AQPs, offering a basis for the development of innovative therapeutic agents for cancer treatment. However, further validation of the identified compounds through experiments is essential for translating these findings into therapeutic applications.Communicated by Ramaswamy H. Sarma.

Repurposing dye ligands as antivirals via a docking approach on viral membrane and globular proteins - SARS-CoV-2 and HPV-16

A series of dye ligands are docked to three different proteins, E and 3a of severe acute respiratory syndrome corona virus 2 (SARS-CoV-2) and E6 of human papilloma virus type 16 (HPV-16) using three different software. A four-level selection algorithm is used based on nonparametric statistics of numerical key values such as the "rank" derived from (i) averaged estimated binding energies (EBEs) and (ii) absolute EBE value of each of the software, (iii) frequency of ranking and (iv) rank of the area-under-curve values (AUCs) from decoy docking. A series of repurposing drugs and known antivirals used in experimental studies are docked for comparison. One dye ligand is ranked best for all proteins using the selection algorithm levels i - iii. Another three dye ligands are ranked top for the proteins individually when using all four levels.

Insight into intermolecular binding mechanism of apatinib mesylate and human alpha-1-acid glycoprotein: combined multi-spectroscopic approaches with in silico

Apatinib mesylate (APM), an oral tyrosine kinase inhibitor, has a good anti-tumor activity in the treatment of various cancers, particularly in advanced non-small cell lung cancer. In this study, the intermolecular binding mechanism between APM and human alpha-1-acid glycoprotein (HAG) was investigated by combining multi-spectroscopic approaches with in silico techniques. The findings revealed that APM gave rise to the fluorescence quenching of HAG by forming a ground-state complex between APM and HAG with a stoichiometric ratio of 1:1, and APM has a moderate affinity for HAG as the binding constant of APM and HAG of approximately 105 M-1, which was larger than the APM-HAG complex. The findings from thermodynamic parameter analysis indicated that the dominant driving forces for the formation of the APM-HAG complex were van der Waals forces, hydrogen bonding and hydrophobic interactions, which were also verified with site-probe studies and molecular docking. The findings from in silico study indicated that APM inserted into the opening of the hydrophobic cavity of HAG, leads to a slight conformational change in the HAG, which was verified by circular dichroism (CD) measurements, that was, the beta sheet level of HAG decreased. Additionally, the results of synchronous and 3D fluorescence spectroscopies confirmed the decline in hydrophobicity of the microenvironment around Trp and Tyr residues. Moreover, some common metal ions such as Cu2+, Mg2+, Fe3+, Ca2+, and Zn2+ could cause the alteration in the binding constant of APM with HAG, leading to the change in the efficacy of APM. It will be expected that these study findings are to provide useful information for further understanding pharmacokinetic and structural modifications of APM.Communicated by Ramaswamy H. Sarma.

Study of nitrogen heterocycles as DNA/HSA binder, topoisomerase inhibitors and toxicological safety

Four new nitrogen-containing heterocyclic derivatives (acridine, quinoline, indole, pyridine) were synthesized and their biological properties were evaluated. The compounds showed affinity for DNA and HSA, with CAIC and CAAC displaying higher binding constants (Kb) of 9.54 × 104 and 1.06 × 106, respectively. The fluorescence quenching assay (Ksv) revealed suppression values ranging from 0.34 to 0.64 × 103 M-1 for ethidium bromide (EB) and 0.1 to 0.34 × 103 M-1 for acridine orange (AO). Molecular docking confirmed the competition of the derivatives with intercalation probes at the same binding site. At 10 μM concentrations, the derivatives inhibited topoisomerase IIα activity. In the antiproliferative assays, the compounds demonstrated activity against MCF-7 and T47-D tumor cells and nonhemolytic profile. Regarding toxicity, no acute effects were observed in the embryos. However, some compounds caused enzymatic and cardiac changes, particularly the CAIC, which increased SOD activity and altered heart rate compared to the control. These findings suggest potential antitumor action of the derivatives and indicate that substituting the acridine core with different cores does not interfere with their interaction and topoisomerase inhibition. Further investigations are required to assess possible toxicological effects, including reactive oxygen species generation.

Molecular docking and dynamics of a dextranase derived from Penicillium cyclopium CICC-4022

This study aimed to investigate the recognition mechanism of dextranase (PC-Edex) produced by Penicillium cyclopium CICC-4022 on dextran. Whole genome information of P. cyclopium CICC-4022 was obtained through genome sequencing technology. The coding information of PC-Edex was determined based on the annotation of the protein-coding genes using protein databases. The three-dimensional structure of PC-Edex was obtained via homology modelling. The active site and binding free energy between PC-Edex and dextran were calculated by molecular docking and molecular dynamics techniques. The results showed that the total sequence length and GC content of P. cyclopium CICC-4022 were 29,710,801 bp and 47.02 %, respectively. The annotation of protein-encoding genes showed that P. cyclopium CICC-4022 is highly active and has many carbohydrate transport and metabolic functions, and most of its proteases are glycolytic anhydrases. Furthermore, the gene encoding PC-Edex was successfully annotated. Molecular dynamics simulations indicated that van der Waals interaction was the main driving force of interaction. Residues Ile114, Asp115, Tyr332, Lys344, and Gln403 significantly promoted the binding between dextran and PC-Edex. In summary, this study explored the active site catalyzed by PC-Edex based on the binding pattern of PC-Edex and dextran. Therefore, this study provides genomic information on dextranase and data supporting the rational modification and enhancement of PC-Edex.

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

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

Rapid Screening of Phenolic Compounds with Anti-Enteritis Activity from Camellia oleifera Oil Using a Smurf Drosophila Model and Molecular Docking Methods

Screening and identifying the active compounds in foods are important for the development and utilization of functional foods. In this study, the anti-enteritis activity of ethanol extract from Camellia oleifera oil (PECS) was quickly evaluated using a Smurf Drosophila model and the metabolomics approach, combined with molecular docking techniques, were performed to rapidly screen and identify compounds with potential anti-enteritis activity in PECS. PECS showed good anti-enteritis activity and inhibited the activity of 5-lipoxygenase (LOX), cyclooxygenase 2 (COX-2) and inducible nitric oxide synthase (iNOS). In particular, wighteone and p-octopamine were newly identified in C. oleifera oil and were proven to have good anti-enteritis activity. The inhibitory activity of kaempferitrin (IC50 = 0.365 mmol L-1) was higher than that of wighteone (IC50 = 0.424 mmol L-1) and p-octopamine (IC50 = 0.402 mmol L-1). Of note, the IC50 value of salazosulfapyridine was 0.810 mmol L-1. Inhibition of LOX activity is likely one of the anti-enteritis mechanisms of PECS. These new findings lay the foundation for further investigations into the underlying mechanisms of anti-enteritis activity in C. oleifera oil.

Targeting Sirtuin 1 for therapeutic potential: Drug repurposing approach integrating docking and molecular dynamics simulations

Identifying novel therapeutic agents is a fundamental challenge in contemporary drug development, especially in the context of complex diseases like cancer, neurodegenerative disorders, and metabolic syndromes. Here, we present a comprehensive computational study to identify potential inhibitors of SIRT1 (Sirtuin 1), a critical protein involved in various cellular processes and disease pathways. Leveraging the concept of drug repurposing, we employed a multifaceted approach that integrates molecular docking and molecular dynamics (MD) simulations to predict the binding affinities and dynamic behavior of a diverse set of FDA-approved drugs from DrugBank against the SIRT1. Initially, compounds were shortlisted based on their binding affinities and interaction analyses to identify safe and promising binding partners for SIRT1. Among these candidates, Doxercalciferol and Timiperone emerged as potential candidates, displaying notable affinity, efficiency, and specificity towards the binding pocket of SIRT1. Extensive evaluation revealed that these identified compounds boast a range of favorable biological properties and prefer binding to the active site of SIRT1. To delve deeper into the interactions, all-atom MD simulations were conducted for 500 nanoseconds (ns). These simulations assessed the conformational dynamics, stability, and interaction mechanism of the SIRT1-Doxercalciferol and SIRT1-Timiperone complexes. The MD simulations illustrated that the SIRT1-Doxercalciferol and SIRT1-Timiperone complexes maintain stability over a 500 ns trajectory. These insightful outcomes propose that Doxercalciferol and Timiperone hold promise as viable scaffolds for developing potential SIRT1 inhibitors, with implications for tackling complex diseases such as cancer, neurodegenerative disorders, and metabolic syndromes.

Discovery of a new dihydroeugenol-chalcone hybrid with cytotoxic and anti-migratory potential: A dual-action hit for cancer therapeutics

Cancer still represents a serious public health problem and one of the main problems related to the worsening of this disease is the ability of some tumors to develop metastasis. In this work, we synthesized a new series of chalcones and isoxazoles derived from eugenol and analogues as molecular hybrids and these compounds were evaluated against different tumor cell lines. This structural pattern was designed considering the cytotoxic potential already known for eugenol, chalcones and isoxazoles. Notably, chalcones 7, 9, 10, and 11 displayed significant activity (4.2-14.5 µM) against two cancer cell lines, surpassing the potency of the control drug doxorubicin. The reaction of chalcones with hydroxylamine hydrochloride provided the corresponding isoxazoles that were inactive against these cancer cells. The dihydroeugenol chalcone 7 showed the most promising results, demonstrating higher potency against HepG2 (CC50: 4.2 µM) and TOV-21G (CC50: 7.2 µM). Chalcone 7 was also three times less toxic than doxorubicin considering HepG2 cells, with a selectivity index greater than 11. Further investigations including clonogenic survival, cell cycle progression and cell migration assays confirmed the compelling antitumoral potential of chalcone 7, as it reduced long-term survival due to DNA fragmentation, inducing cell death and inhibiting HepG2 cells migration. Moreover, in silico studies involving docking and molecular dynamics revealed a consistent binding mode of chalcone 7 with metalloproteinases, particularly MMP-9, shedding light on its potential mechanism of action related to anti-migratory effects. These significant findings suggest the inclusion of compound 7 as a promising candidate for future studies in the field of cancer therapeutics.

Structure-based molecular docking and molecular dynamics simulations study for the identification of dipeptidyl peptidase 4 inhibitors in type 2 diabetes

Inhibition of dipeptidyl peptidase-4 (DPP4) activity has emerged as a promising therapeutic approach for the treatment of type 2 diabetes mellitus (T2DM). Bioinformatics-driven approaches have emerged as crucial tools in drug discovery. Molecular docking and molecular dynamics (MD) simulations are effective tools in drug discovery, as they reduce the time and cost associated with experimental screening. In this study, we employed structure-assisted in-silico methods, including molecular docking and MD simulations, to identify SRT2183, a small molecule that may potentially inhibit the activity of DPP4 enzyme. The interaction between the small molecule "SRT2183" and DPP4 exhibited a binding affinity of -9.9 Kcal/Mol, leading to the formation of hydrogen bonds with the amino acid residues MET348, SER376, and THR351 of DPP4. The MD simulations over a period of 100 ns indicated stable protein-ligand interactions, with no significant conformational rearrangements observed within the simulated timeframe. In conclusion, our results suggest that the small molecule SRT2183 may have the potential to inhibit the DPP4 enzyme and pave the way for the therapeutics of T2DM.Communicated by Ramaswamy H. Sarma.

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.

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.

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.

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.

In Silico Strategies to Predict Anti-aging Features of Whey Peptides

We have analysed the in silico potential of bioactive peptides from cheese whey, the most relevant by-product from the dairy industry, to bind into the active site of collagenase and elastase. The peptides generated from the hydrolysis of bovine β-lactoglobulin with three proteases (trypsin, chymotrypsin, and subtilisin) were docked onto collagenase and elastase by molecular docking. The interaction models were ranked according to their free binding energy using molecular dynamics simulations, which showed that most complexes presented favourable interactions. Interactions with elastase had significantly lower binding energies than those with collagenase. Regarding the interaction site, it was found that four bioactive peptides were positioned in collagenase's active site, while six were found in elastase's active site. Among these, the most we have found one promising collagen-binding peptide produced by chymotrypsin and two for elastase, produced by subtilisin and chymotrypsin. These in silico results can be used as a tool for designing further experiments aiming at testing the in vitro potential of the peptides found in this work.

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.