3D-QSAR Models Research Articles

Pharmacophore-based 3D-QSAR modeling, virtual screening, docking, molecular dynamics and biological evaluation studies for identification of potential inhibitors of alpha-glucosidase.

Alpha-glucosidase enzyme is considered an important therapeutic target for controlling hyperglycemia associated with type 2 diabetes. Novel scaffolds identified as potential alpha-glucosidase inhibitors from the Maybridge library utilizing pharmacophore modeling, molecular docking and biological evaluation are reported in this manuscript. A total of 51 xanthone series scaffolds previously reported as alpha-glucosidase inhibitors were collected and used as training and test sets. These sets were employed to develop and validate a pharmacophore-based 3D-QSAR model with statistically meaningful results using Schrodinger software. The model showed a high F value (F, 80.1) at five component partial least square factors, a high cross-validation coefficient (Q2, 0.66) and a good correlation coefficient (R2, 0.95). Pearson correlation coefficient (r) of 0.8400 indicated a greater degree of confidence in the model. Subsequently, virtual screening was performed with PHASE module of Schrodinger software using the above model to identify novel alpha-glucosidase inhibitors, and mapped compounds were evaluated for their interactions with the protein. The X-ray co-crystallised structure of the alpha-glucosidase protein in complex with acarbose (PDB Code: 5NN8) was used for molecular docking analysis using GLIDE module and a total of eight compounds were further selected for biological evaluation. Molecular dynamics analysis using GROMACS software was performed in the active site of alpha-glucosidase protein to gain insights into binding mechanism of the four active compounds which were finally found to exhibit inhibitory activity in the biological assay.

Design of some phthalazine molecules as novel VEGFR-2 target inhibitors through 3D-QSAR modeling, molecular docking and dynamic simulation and pharmacokinetics profiling

AbstractBreast cancer is one of the dominant cause of cancer-related mortality in females, with an incidence of approximately 1.3 million cases annually, necessitating the development of effective therapeutic strategies. In this study, 3D-QSAR models were reported based on Phthalazine derivatives as VEGFR-2 inhibitors. The activities of these derivatives were correlated with the steric (S), electrostatic (E), hydrogen bond acceptor (A), and donor (D), and hydrophobic (H) fields, which served as critical parameters in model development. Statistical studies of these models showed that the best models are; CoMFA_S (Q2 = 0.623, R2 = 0.941), and CoMSIA_E + D (Q2 = 0.615, R2 = 0.977). Based on the insights from the model fields and docking simulation of the template (compound 17), twelve molecules were designed. These novel molecules exhibited stronger potency compared to the template and the standard, Sorafenib. Compound 17A emerged as the most potent, with pIC50 = 5.98, for CoMFA_S and 5.85, for CoMSIA_E + D, and a strong docking affinity of − 97.271 kcal/mol, therefore subjected to a 100-ns MD simulation. Results indicate better interaction and stabilizing potential over Sorafenib, due to the lower RMSD, RMSF, Rg, values and favorable hydrogen bond analyses. These conclusions were validated by Gibbs free energy analysis and MM-GBSA calculations, revealing a more favorable interaction free energy of − 18.48 kcal/mol related to Sorafenib. Furthermore, these designed compounds demonstrated promising pharmacokinetic profiles.

Design, Synthesis, and 3D-QASR of Oxazoline Derivatives Containing an S-S Moiety as Potential Acaricide.

To mitigate the detrimental effects of agricultural pest mites on crop yield, an active substructure splicing strategy was employed to modify etoxazole by introducing an S-S moiety. The target products were obtained efficiently via a bilateral disulfurating reagent (DSMO), which was developed by our group. The leaf dip method was used to evaluate the activities of the designed target compounds against the eggs and larvae of the spider mite (Tetranychus cinnabarinus). Most of the target compounds exhibited good efficacy in controlling the larvae and eggs of T. cinnabarinus. Based on these results, a three-dimensional quantitative structure-activity relationship (3D-QSAR) model was established to guide the construction of compound 7l. Notably, compound 7l exhibited a better activity against T. cinnabarinus eggs (LC50 = 0.0035 mg/L) compared to etoxazole (LC50 = 0.2990 mg/L). Greenhouse bioassays indicated that compound 7l exhibits excellent acaricidal activity against egg of T. cinnabarinus, which is better than the etoxazole at 1.0 mg/L. Additionally, some of the compounds showed inhibitory effects against Dickeya zeae (D. zeae), Xanthomonas campestris pv campestris (Xcc), Xanthomonas oryzae pvoryza (Xoo), and Xanthomonas oryzae pvoryzicola (Xoc). Furthermore, compounds 7l not only exhibited relatively potent against Plutella xylostella activities (LC50 = 24.0 mg/L) but also had low toxicity (LC50 > 11.0 μg/bee) to Apis mellifera. In conclusion, the current experimental results suggest that oxazoline derivatives containing an S-S moiety have the potential to serve as lead compounds for the development of novel acaricide agents.

Synthesis of Novel Indolyl Aryl Sulfone-clubbed Hydrazone Derivatives as Potential HIV-1 Non-Nucleoside Reverse Transcriptase Inhibitors: Molecular Modeling and QSAR Studies.

Non-Nucleoside Reverse Transcriptases Inhibitors (NNRTIs) are among the most extensively studied enzymes for understanding the biology of Human Immunodeficiency Viruses (HIV) and designing inhibitors for managing HIV infections. Indolyl aryl sulfones (IASs), an underexplored class of potent NNRTIs, require further exploration for the development of newer drugs for HIV. In this context, we synthesized a series of novels by Indolyl Aryl Sulfones with a hydrazone moiety at the carboxylate site of the indole nucleus. A 2D-QSAR model was developed to predict Reverse Transcriptase inhibitory activity against wild-type RT (WT-RT) enzyme. The model was successfully applied to predict the HIV-1 inhibitory activity of known Indolyl Aryl Sulfones. Considering the reliability, robustness, and reproducibility of the 2D-QSAR model, we made an in-silico prediction of the RT inhibition for our synthesized compounds (1-14). Molecular docking and dynamics simulations established our synthesized Indolyl Aryl Sulfones, particularly compounds 23, 24, and 28, as effective NNRTIs by stabilizing HIV reverse transcriptase's structure. Binding energy calculations revealed compound 28 as the strongest inhibitor (-43.21 ± 0.09 kcal/mol), followed by 23 (-40.94 ± 0.10 kcal/mol) and 24 (-39.18±0.08 kcal/mol), emphasizing their binding affinity towards HIV reverse transcriptase. In summary, the synthesized Indolyl Aryl Sulfones, particularly compounds 23, 24, and 28, demonstrate significant potential as Non-Nucleoside Reverse Transcriptase Inhibitors (NNRTIs) against HIV. These results highlight the promising role of these compounds in developing novel NNRTIs for managing HIV infections.

Integration of 3D-QSAR, molecular docking, and machine learning techniques for rational design of nicotinamide-based SIRT2 inhibitors

Selective inhibitors of sirtuin-2 (SIRT2) are increasingly recognized as potential therapeutics for cancer and neurodegenerative diseases. Derivatives of 5-((3-amidobenzyl)oxy)nicotinamides have been identified as some of the most potent and selective SIRT2 inhibitors reported to date (​Ai et al., 2016​; ​Ai et al., 2023​, ​Baroni et al., 2007​). In this study, a 3D-QSAR (3D-Quantitative Structure-Activity Relationship) model was developed using a dataset of 86 nicotinamide-based SIRT2 inhibitors from the literature, along with GRIND-derived pharmacophore models for selected inhibitors. External validation parameters emphasized the reliability of the 3D-QSAR model in predicting SIRT2 inhibition within the defined applicability domain. The interpretation of the 3D-QSAR model facilitated the generation of GRIND-derived pharmacophore models, which in turn enabled the design of novel SIRT2 inhibitors. Furthermore, based on molecular docking results for the SIRT1–3 isoforms, two classification models were developed: a SIRT1/2 model using the Naive Bayes algorithm and a SIRT2/3 model using the k-nearest neighbors algorithm, to predict the selectivity of inhibitors for SIRT1/2 and SIRT2/3. External validation parameters of the selectivity models confirmed their predictive power. Ultimately, the integration of 3D-QSAR, selectivity models and prediction of ADMET properties facilitated the identification of the most promising selective SIRT2 inhibitors for further development.

Design of novel potent selective survivin inhibitors using 2D-QSAR modeling, molecular docking, molecular dynamics, and ADMET properties of new MX-106 hydroxyquinoline scaffold derivatives

Given the critical role of survivin (BIRC5) in tumor cell regulation, developing novel inhibitors represents a promising approach for cancer therapy. This study details the design of innovative survivin inhibitors based on the hydroxyquinoline scaffold of our previously reported lead compound, MX-106. Our study identified nine compounds whose inhibitory activity is expected to be superior to that of the most active molecule in the series. These compounds demonstrated potent suppression of MDA-MB-435 breast cancer cell proliferation in vitro and exhibited enhanced metabolic stability compared to the series' most active member. To evaluate these derivatives as potential survivin inhibitors, we employed a multi-faceted approach combining 2D-QSAR methods, molecular docking, molecular dynamics, and ADMET property assessment. Our molecular modeling studies led to the design of nine novel compounds (Pred1-Pred9) predicted to exhibit potent survivin inhibitory activity based on MLR models. To assess their suitability as drug candidates, we recommend a thorough evaluation of their ADMET properties. These compounds hold promise as innovative anticancer agents targeting survivin, similar to the established MX-106.

Synthesis and Antifungal Activities of Glucosamine Aromatic Derivatives Against Four Phytopathogenic Fungi of Crops.

A series of diversified glucosamine derivatives (3a-3y) was synthesized and their antifungal activity was examined against four kinds of phytopathogens, Fusarium graminearum (F. graminearum), Fusarium moniliforme (F. moniliforme), Curvularia. lunata (C. lunata), and Rhizoctonia solani (R. solani) which cause seriously economic losses worldwide by affecting crops. The compound 3o showed remarkable antifungal activity against F. graminearum with EC50 value of 3.96 μg/mL, compared to the standard drug triadimefon (10.1 μg/mL). 3D-QSAR model with the statistically recommended values (r2=0.915, q2=0.872) showed that positive charge group or bulky group in the benzyl ring was favorable for the antifungal activity. Enzyme activity assays confirmed that 3o had a moderate inhibition of trehalase with inhibition rate of 51.4 % at 5 μg/mL, which is comparable to those of commercial inhibitor validamycin A with inhibition rate of 83.3 %. Molecular docking analysis revealed that 3o also had a hydrogen bond interaction with key amino acid residue compared to validoxylamine.

Machine learning approaches in designing anti-HIV nitroimidazoles: 2D/3D QSAR, kNN-MFA, docking, dynamics, PCA analysis and MMGBSA studies

In this study, newly synthesized 20 nitroimidazole derivatives were subjected to 2D and 3D Quantitative Structure-Activity Relationship (QSAR) study to investigate their anti-HIV activity against both ROD and IIIB strains. Later, proposed hypothesis was virtually proved by further in-silico studies. In statistically significant 2D-QSAR models r2 values for IIIB strains 0.9241 and for ROD strains 0.9412 with corresponding q2 values of 0.7706 and 0.8299, were obtained, respectively. Different models were constructed using three different kNN-MFA 3D QSAR approaches such as SW-FB, SA score, and GA. By using the generated hypothesis, newer analogues of nitroimidazole derivatives was designed and molecular modelling studies were conducted to prove the hypothesis. The three molecules were displayed the good docking scores compared to the reference molecule. The stabilities of docked complexes were analyzed by MD simulations and MMGB/SA calculations. These results offer insightful design guidance for novel anti-HIV compounds synthesis and suggest interesting directions for future pharmaceutical research.

Synthesis, antimicrobial, anticancer activity, 3D QSAR, ADMET properties, and in silico target fishing of novel N,N-disubstituted chloroacetamides

The recent FDA approval of afatanib, ibrutinib, and osimertinib, which covalently bind to specific cysteine residues in target kinases, has renewed interest in covalent drug discovery. Besides α,β-unsaturated carbonyls, chloroacetamides have emerged as popular warheads for designing targeted covalent inhibitors. In this study, we synthesized thirteen N,N-disubstituted chloroacetamides (1–13) by acylating secondary amines with chloroacetyl chloride, selecting substituents to provide a wide range of lipophilicity. We evaluated their anticancer and antimicrobial activity, finding five compounds with significant cytotoxicity against HeLa, K562, and A549 cell lines (IC50 <10 μM). Notably, compound 10 activated caspases 3, 8, and 9, promoting both intrinsic and extrinsic apoptotic pathways, while compounds 9–12 were strong apoptosis inducers. A 3D QSAR model showed that aromatic substituents on nitrogen atoms reduced HeLa potency, whereas the overall molecular shape had a positive effect. ChemBL and pharmacophoric similarity searches suggested potential anticancer targets, including alcohol dehydrogenase (ADH), aldehyde dehydrogenase (ALDH), glycogen synthase kinase-3β, and calmodulin. Docking studies indicated that chloroacetamides bind to ADH and ALDH via hydrogen bonds and hydrophobic interactions. Pharmacokinetics predictions suggest that chloroacetamides are druglike molecules with promising ADMET properties.

Synthesis, antifungal activity, and 3d-QSAR study of L-carvone-based pyrazole-oxime ester compounds

Natural products can provide versatile substructures with potential bioactivity and biocompatibility for exploring bioactive compounds. Herein, to explore novel natural product-derived antifungal agents, 21 unreported L -carvone-based pyrazole-oxime ester compounds 6a-6u were synthesised using L-carvone as raw material, and structurally characterised by means of FT-IR,1H NMR,13C NMR, and HRMS. The results of the in vitro bioactivity tests showed that the target compounds exhibited certain antifungal activity against the eight tested plant fungi at the concentration of 50 mg/L, especially for Physalospora piricola. The inhibition rates of compounds 6e (R = m-Cl) and 6c (R = m-F) against P. piricola were 88.3% and 83.9%, respectively, both better than that of the positive control chlorothalonil. Compound 6e (R= m-Cl) with the most significant antifungal activity deserves further investigation as the potential leading compound. In addition, the structure-activity relationships (SARs) of the target compounds were investigated by establishing an effective three-dimensional quantitative structure-activity relationship (3D-QSAR) model.

Integrating computational 3D-QSAR and pharmacophore modelling in diverse natural phytochemicals library for targeted therapy against breast cancer estrogen receptors

Breast cancer stands as a pervasive global health challenge, profoundly impacting the physical and emotional well-being of individuals. The relentless growth of malignant cells within breast tissues necessitates comprehensive research into the disease's origin, early detection, and treatment strategies. This study focused on constructing pharmacophores and 3D-QSAR models to dissect the crucial structure attributes essential for inhibiting Estrogen receptors. By employing ligand-based pharmacophore modeling and Atom-based-3D-QSAR techniques within the Schrödinger Phase module, we analyzed the inhibitory activity of 202 natural compounds and Tamoxifen as the control drug. To identify promising candidates, five molecules (Genistein, Coumestrol, Apigenin, Emodin, and Daidzein) were strategically chosen based on prediction from the 3D-QSAR pharmacophore model. These molecules are further assessed through model validation and virtual screening. The generated pharmacophore model (ADHR.10) reveals key features like hydrogen bond donors (HBD), hydrogen bond acceptors (HBA), and hydrophobic interactions. The resulting 3D-QSAR model predicted and stability was validated through the Xternal validation plus tool. The ADHR.10 model guided the systematic screening of natural compounds, resulting in the identification of the top five hits with promising pharmacological activity. Molecular docking scores demonstrated the compound's binding affinity with ESR1 (PDB ID: 6PSJ) and ESR2 (PDB ID: 1QKM). One standout compound, Coumestrol, displayed an exceptional binding affinity with ESR2 outperforming Tamoxifen. The top compounds exhibited both strong binding and stability, making them a promising candidate. Furthermore, Molecular Dynamics Simulation (MDS) demonstrated Coumestrol's superior stability compared to the control drug against the ESR1 and ERS2 proteins. Coumestrol exhibits lower average fluctuation in RMSD and residue-specific dynamics (RMSF) indicating stability than control. Specifically, designed compounds, rooted in natural sources, demonstrated excellent potential as breast cancer treatment candidates. These findings highlight them as promising lead candidates for the development of targeted breast cancer therapies and emphasize the potential of computational approaches in discovering new therapeutic avenues.

Identification of Marine-Derived SLC7A11 Inhibitors: Molecular Docking, Structure-Based Virtual Screening, Cytotoxicity Prediction, and Molecular Dynamics Simulation.

The search for anticancer drugs that target ferroptosis is a promising avenue of research. SLC7A11, a key protein involved in ferroptosis, has been identified as a potential target for drug development. Through screening efforts, novel inhibitors of SLC7A11 have been designed with the aim of promoting ferroptosis and ultimately eliminating cancer cells. We initially screened 563 small molecules using pharmacophore and 2D-QSAR models. Molecular docking and ADMET toxicity predictions, with Erastin as a positive control, identified the small molecules 42711 and 27363 as lead compounds with strong inhibitory activity against SLC7A11. Further optimization resulted in the development of a new inhibitor structure (42711_11). Molecular docking and ADMET re-screening demonstrated successful fragment substitution for this small molecule. Final molecular dynamics simulations also confirmed its stable interaction with the protein. These findings represent a significant step towards the development of new therapeutic strategies for ferroptosis-related diseases.

Unveiling the potential of novel 5α-reductase inhibitors via ligand based drug design, molecular docking and ADME predictions to manage BPH

Benign prostatic hyperplasia (BPH), a prevalent condition among elderly males characterized by the non-cancerous enlargement of the prostate gland is due to the increased stromal and epithelial cell numbers. The enlargement is driven by an active dihydrotestosterone (DHT), synthesized from its prohormone testosterone under the catalytic effect of 5α-reductase Type-II (5-AR2) enzyme. To reduce the increased DHT levels and ultimately to control prostate growth, inhibition of the 5-AR represent an interesting therapeutic target. The 3D crystallography structure 5-AR2, a member of the steroid 5-AR family belonging to the class of oxidoreductase has been resolved recently and opened the door to develop selective novel inhibitors of 5-AR Type-II isoform using molecular modeling techniques. The Force field and Gaussian-field three-dimensional quantitative structure–activity relationship (3D-QSAR) models have been developed using 42 selective 5-AR2 inhibitors belonging to chemical class of steroidal androstene. Partial least squares analysis produced statistically significant model with R2training = 0.9367, 0.9459 and predictability Q2test = 0.7233, 0.8595. Developed 3D-QSAR model include steric, electrostatic, hydrophobic, and hydrogen bond acceptor and donor field indicators, whereas the potential field contributions indicated the importance of steric feature in governing their biological activity. Protein-ligand interaction pattern analysis revealed that amino acid residues GLU57, ARG114, TYR91 present in the active site of 5-AR2 are crucial for lower energy complexes with good binding affinity. Identified hits were finally adjudged for their druggability by determining in-silico pharmacokinetic parameters. Further, RMSD, binding free energy calculations and post MD analysis demonstrated the enhanced binding affinity with better ΔGbind value (-79.6 ± 3.9 kcal/mol) of identified ligand A-10 than the reference molecule finasteride (-69.13 ± 4.69 kcal/mol). Combined approach of ligand-based and structure-based models have provided an improved understanding of the structural properties of androstene class that may be further used to develop novel 5-AR2 inhibitors to be useful in BPH.

Unveiling structural determinants for FXR antagonism in 1,3,4-trisubstituted-Pyrazol amide derivatives: A multi-scale in silico modelling approach

Non-alcoholic fatty liver disease (NAFLD) is a growing global health concern due to its potential to progress into severe liver diseases. Targeting the bile acid receptor FXR has emerged as a promising strategy for managing NAFLD. Building upon our previous research on FXR partial agonism, the present study investigates a series of 1,3,4-trisubstituted-pyrazol amide derivatives as FXR antagonists, aiming to delineate the structural features for antagonism. By means of 2D-QSAR (quantitative structure-activity relationships) modelling techniques, we elucidated the key structural elements responsible for the antagonistic properties of these derivatives. We then employed QPhAR, an open-access software, to identify key molecular features within the compounds that enhance their antagonistic activity. Additionally, 3D-QSAR modelling allowed us to analyse the steric and electrostatic fields of aligned 3D structures, further refining our understanding of structure-activity relationships. Subsequent molecular dynamics simulations provided insights into the binding mode interactions between the compounds and FXR, with varying potencies, confirming and complementing the findings from 2D-QSAR, pharmacophore, and 3D-QSAR modelling. Particularly, our study highlighted the significance of hydrophobic interactions in conferring potent antagonism by the 1,3,4-trisubstituted-pyrazol amide derivatives against FXR. Overall, this work underscores the potential of 1,3,4-trisubstituted-pyrazol amides as FXR antagonists for NAFLD treatment. Notably, our reliance on open-access software fosters reproducibility and broadens the accessibility of our findings.

3D-QSAR, Pharmacophore Modeling, ADMET, and DFT Studies of Halogenated Conjugated Dienones as Potent MAO-B Inhibitors.

It has been reported that the extension of conjugation in chalcone scaffolds considerably enhanced the potency, selectivity, reversibility, and competitive mode of MAO-B inhibition. In this study, using the experimental results of IC50 values of fifteen halogenated conjugated dienone derivatives (MK1-MK15) against MAO-B, we developed a 3DQSAR model. Further, we created a 3D pharmacophore model in active compounds in the series. The built model selected three variables (G2U, RDF115m, RDF155m) among the 653 AlvaDesc molecular descriptors, with a r2 value of 0.87 and a Q2 cv for cross-validation equal to 0.82. The three variables were mostly associated with the direction of symmetry and the likelihood of discovering massive atoms at great distances. The evaluated molecules exhibited a good correlation between experimental and predicted data, indicating that the IC50 value of the structure MK2 was related to the interatomic distances of 15.5 Å between bromine and chloro substituents. Furthermore, the molecules in the series with the highest activity were those with enhanced second component symmetry directional index from the 3D representation, which included the structures MK5 and MK6. Additionally, a pharmacophore hypothesis was developed and validated using the decoy Schrodinger dataset, with an ROC score of 0.87 and an HHRR 1 fitness score that ranged from 2.783 to 3.00. The MK series exhibited a significant blood-brain barrier (BBB) permeability, according to exploratory analyses and in silico projections, and almost all analogues were expected to have strong BBB permeability. Further DFT research revealed that electrostatics were important in the interactions with MAO-B.

Identification of tuberculosis inhibitors through QSAR-based virtual screening and molecular dynamics simulation of novel pyrimidine derivatives

Tuberculosis (TB), caused by Mycobacterium tuberculosis (Mtb), is the leading cause of death due to antimicrobial resistance, highlighting the urgency for innovative solutions and required the development of new drugs for TB treatment. In this study, we have conducted virtual screening and 2D quantitative structure activity relationship (2D-QSAR) models to analyze a set of fifty pyrimidine derivatives, aiming to uncover potential inhibitors for TB. The dataset is divided into a training set of thirty-eight molecules and a test set, using multiple linear regression (MLR). The key metrics such as R2 = 0.82, R2adj = 0.78, Ntest = 12, and R2test = 0.70, demonstrate the robustness of the built 2D-QSAR model. Leveraging the applicability domain of the model, using the Williams plot, databases of newer pyrimidine derivatives were created for drug-like property screening and activity prediction (pIC50) in TB treatment. Subsequently, molecular docking high-throughput virtual screening (HTVS), and dynamics simulations were employed to predict docking poses within Mtb kinases A and B (PDB: 6B2P). Detailed analysis revealed effective interactions between active amino acid sites in the Mtb pocket and the novel design drug molecules, sustaining the stability of their complexes.

Robustaflavone as a novel scaffold for inhibitors of native and auto-proteolysed human neutrophil elastase

ABSTRACT Human neutrophil elastase (HNE) plays a key role in initiating inflammation in the cardiopulmonary and systemic contexts. Pathological auto-proteolysed two-chain (tc) HNE exhibits reduced binding affinity with inhibitors. Using AutoDock Vina v1.2.0, 66 flavonoid inhibitors, sivelestat and alvelestat were docked with single-chain (sc) HNE and tcHNE. Schrodinger PHASE v13.4.132 was used to generate a 3D-QSAR model. Molecular dynamics (MD) simulations were conducted with AMBER v18. The 3D-QSAR model for flavonoids with scHNE showed r 2 = 0.95 and q 2 = 0.91. High-activity compounds had hydrophobic A/A2 and C/C2 rings in the S1 subsite, with hydrogen bond donors at C5 and C7 positions of the A/A2 ring, and the C4’ position of the B/B1 ring. All flavonoids except robustaflavone occupied the S1’-S2’ subsites of tcHNE with decreased AutoDock binding affinities. During MD simulations, robustaflavone remained highly stable with both HNE forms. Principal Component Analysis suggested that robustaflavone binding induced structural stability in both HNE forms. Cluster analysis and free energy landscape plots showed that robustaflavone remained within the sc and tcHNE binding site throughout the 100 ns MD simulation. The robustaflavone scaffold likely inhibits both tcHNE and scHNE. It is potentially superior to sivelestat and alvelestat and can aid in developing therapeutics targeting both forms of HNE.

Discovery of Novel Lysine Methyltransferase (SMYD3) Inhibitors by Utilizing 3D-QSAR, Molecular Docking and Molecular Dynamics Simulation

Aim: To investigate novel isoxazole amide SMYD3 inhibitors as adjuvant anticancer agents for multiple cancers. Background: SET and MYND Domain-Containing Protein 3 is a hopeful therapeutic target for breast, liver, colon, and prostate cancer. Objective: Novel SMYD3 inhibitors were predicted by the 3D-QSAR models. Methods: In this present work, 3D-QSAR, molecular docking and molecular dynamics (MD) simulations were performed on a series of isoxazole amides-based SMYD3 inhibitors. Results: Molecular docking revealed residues important to protein-compound interactions, indicating that SMYD3 inhibitors have a strong affinity with and bind to key protein residues such as TYR239, MET190, LYS297 and VAL368. The molecular docking results were further validated by molecular dynamics simulations. Conclusion: The above information provided significant guidance for the design of novel SMYD3 inhibitors.

Chemical Predictive Modelling and Natural Product-based Divergent Synthesis - Design of Type B PPAPs with Nanomolar Activities against MRSA.

In response to the pressing global challenge of antibiotic resistance, time efficient design and synthesis of novel antibiotics are of immense need. Polycyclic polyprenylated acylphloroglucinols (PPAP) were previously reported to effectively combat a range of gram-positive bacteria. Although the exact mode of action is still not clear, we conceptualized a late-stage divergent synthesis approach to expand our natural product-based PPAP library by 30 additional entities to perform SAR studies against methicillin-resistant Staphylococcus aureus (MRSA). Although at this point only data from cellular assays are available and understanding of molecular drug-target interactions are lacking, the experimental data were used to generate 3D-QSAR models via an artificial intelligence training and to identify a common pharmacophore model. The experimentally validated QSAR model enabled the estimation of anti-MRSA activities of a virtual compound library consisting of more than 100,000 in-silico generated B PPAPs, out of which the 20 most promising candidates were synthesized. These novel PPAPs revealed significantly improved cellular activities against MRSA with growth inhibition down to concentrations less than 1 μm.

Discovery of Novel Acethydrazide-Containing Flavonol Derivatives as Potential Antifungal Agents.

In this study, a series of novel hydrazide-containing flavonol derivatives was designed, synthesized, and evaluated for antifungal activity. In the in vitro antifungal assay, most of the target compounds exhibited potent antifungal activity against seven tested phytopathogenic fungi. In particular, compound C32 showed the best antifungal activity against Rhizoctonia solani (EC50 = 0.170 μg/mL), outperforming carbendazim (EC50 = 0.360 μg/mL) and boscalid (EC50 = 1.36 μg/mL). Compound C24 exhibited excellent antifungal activity against Valsa mali, Botrytis cinerea, and Alternaria alternata with EC50 values of 0.590, 0.870, and 1.71 μg/mL, respectively. The in vivo experiments revealed that compounds C32 and C24 were potential novel agricultural antifungals. 3D quantitative structure-activity relationship (3D-QSAR) models were used to analyze the structure-activity relationships of these compounds. The analysis results indicated that introducing appropriate electronegative groups at position 4 of a benzene ring could effectively improve the anti-R. solani activity. In the antifungal mechanism study, scanning electron microscopy and transmission electron microscopy analyses revealed that C32 disrupted the normal growth of hyphae by affecting the structural integrity of the cell membrane and cellular respiration. Furthermore, compound C32 exhibited potent succinate dehydrogenase (SDH) inhibitory activity (IC50 = 8.42 μM), surpassing that of the SDH fungicide boscalid (IC50 = 15.6 μM). The molecular dynamics simulations and docking experiments suggested that compound C32 can occupy the active site and form strong interactions with the key residues of SDH. Our findings have great potential for aiding future research on plant disease control in agriculture.