Amino Acid Interactions Research Articles

EMIM] [OAc]: An Efficient Ionic Liquid Medium for the Synthesis of New 4-(furan/pyrrole/thiophene-2-yl)-3, 4-dihydro-1H-chromeno [4,3-d] pyrimidine-2,5-diones and Molecular Docking Studies

Abstract: An efficient synthesis of Chromeno[b]pyrimidine derivatives 4 has been achieved by treating 4-hydroxy-2H-chromen-2-one 1, furan-2-carbaldehyde / 1H-pyrrole-2-carbaldehyde/ thiophene-2- carbaldehyde 2, and urea/thiourea 3 at 65-70 °C for 90-120 min using 1-Ethyl-3-methylimidazolium acetate as ionic liquid and medium with good yields 86-90%. This synthetic method has numerous advantages, including high yields, a simple protocol, environmental friendliness, brief reaction times, and mild reaction conditions. Using a catalytically active ionic liquid as the medium eliminates the need for a catalyst and a solvent. In this study, the docking score of the synthesized compounds was found to be between -8 to -9 kcal/mol similar to the co-crystal. Additionally, the compounds maintained their amino acid interactions with Tyr 281 (coagulation protein; 6WV3) and Thr 179 (tubulin polymerization protein; 5LYJ.pdb).

Elucidating the E‐Cadherin⋯ADTC5 Interactions: A Theoretical Examination of Amino Acid Active Site Binding on the Electronic Level via Density Functional Theory

AbstractThe presence of E‐cadherin⋯E‐cadherin interactions in the intercellular space (paracellular pathway) poses a notable limitation in drug delivery across the blood‐brain barrier (BBB). ADTC5 peptide has shown promising results in improving drug delivery across the BBB by modulating E‐cadherin⋯E‐cadherin interactions. However, the study of E‐cadherin⋯ADTC5 amino acid interactions using quantum mechanics approach has not been observed clearly. Herein, we observed the interaction between E‐cadherin⋯ADTC5 amino acids using density functional theory (DFT). Natural bond orbital (NBO), quantum theory of atoms in molecules (QTAIM), and reduced density gradient (RDG) analysis are performed to study the non‐covalent interaction in detail. The Arg55⋯Asp2 shows the strongest interaction between E‐cadherin⋯ADTC5 modulation, indicated by the highest stabilization energy (E(2)), and hydrogen bonding energy (EHB) about 22.04 and −6.90 kcal/mol, respectively. This interaction is dominated by hydrogen bonding. Such advancements could lead to significant improvements in therapeutic strategies for neurodegenerative diseases, where effective drug delivery across the BBB remains a major challenge.

Design and Synthesis of Ester Linked 1,2,3‐Triazole Quinoline Derivatives with Pancreatic β Cells Protective Activity against Oxidative Stress and Endoplasmic Reticulum Stress for Better Management of Type II Diabetes Mellitus

AbstractUnresolved endoplasmic reticulum (ER) stress and oxidative stress lead to the pathogenesis of type II diabetes mellitus (DM). Connecting links between the ER stress and oxidative stress pathways might play an important role in treatment and pathogenesis of diabetes. Here, we used network pharmacology approach to find the target proteins linking the ER stress and oxidative stress pathways. CHOP emerged as a hub protein from our results and was targeted by 16 newly designed and synthesized ester linked 1,2,3‐triazole quinoline derivatives by molecular docking. Drug likeliness prediction studies revealed all compounds as good druggable candidates. Compounds 5b (R = H, R1 = F), 5j (R = CH3, R1 = F), 5m (R = OCH3, R1 = H), and 5n (R = OCH3, R1 = F) were found to have considerable binding energies and active site amino acid interactions with CHOP. We further showed that compounds 5b, 5m, and 5n exhibited low toxicity with more than 50% cell survival and low IC50 values. These were therefore subjected to evaluate their effects on ER stress and oxidative stress. Finally, compound 5n (R = OCH3, R1 = F) was found to alleviate ER stress and is also a good antioxidant. Identification of such targets and compounds effective in improving ER stress and oxidative stress may provide new insights in the development of therapies and management of T2DM.

B-124 Structure-based Variant Effect Prediction and Design of Functional CYP2C9 Variants by Virtual Evolution

Abstract Background The decryption of massive variants of uncertain significance (VUS) discovered by sequencing poses the main challenge in the post-sequencing era. VUS also resulted in a particular problem in the field of pharmacogenomics, which can be epitomized by drug-metabolizing enzymes, such as CYP2C9. Therefore, an accurate model that incorporates the inner connection between massive protein variants and their function alterations is crucial for clinical annotation of human variome and the virtual evolution of enzyme engineering for biotherapeutics. Methods We developed a model named variant effect recognition network for CYP2C9 (vERnet-P), which learned features from AlphaFold2-predicted protein structures and predicted the enzyme activity of missense single-nucleotide variants in CYP2C9. The two crucial strategies of vERnet-P are the construction of amino acid interaction networks and the application of deep learning. Therefore, vERnet-P leveraged highly accurate protein structures predicted by AlphaFold2, combined with novel techniques for enriching and capturing useful information. Based on the accurate and preemptive prediction of CYP2C9 variants, we performed the saturation mutation prediction on several sites of CYP2C9 to identify new variants with the expected function. Furthermore, the drug metabolic activities of these newly identified variants were investigated with two probe drugs by in vitro metabolic activity assessments. Results An accuracy of up to 93.5% for the classification of activity levels was yielded in the testing dataset. In addition, the tasks for recognizing the high-activity and low-activity variants both achieved 93.5% accuracies, demonstrating that vERnet-P truly learned the features related to enzyme activity, rather than the selection bias to one kind of samples. Strikingly, the AUC values of the ROC and the PR reached 0.971 and 0.966 respectively in the testing cohort for vERnet-P. vERnet-P achieved the strongest agreement with massively parallel assessments relative to the other 8 computational variant effect predictors in the task of predicting CYP2C9 variant enzyme activity. We explored 6 mutant sites in CYP2C9 by using vERnet-P to perform saturation mutation prediction and found 12 novel variants with a high possibility of activity changing. We identified 6 variants with most likely increased activity by using the prediction of wild-type as a cutoff, consequently, 6 variants with most likely decreased activity were selected. According to these 12 discovered variants, 10 were strongly confirmed by the in vitro metabolic activity assays of both probe drugs. Conclusions vERnet-P achieved state-of-the-art performance in predicting the CYP2C9 variant enzyme activity. The preemptive prediction for CYP2C9 variants can efficiently provide the clinical drug dosing guideline. Furthermore, by saturating mutation prediction on several sites, our results indicated the evolutionary direction of CYP2C9 enzyme activity and discovered some brand-new CYP2C9 variants with ultra-strong functional alterations, which have not previously been reported. The results of in vitro metabolic activity assessment were highly consistent with our in silico prediction, indicating the potential of AI models for inferring evolutionary direction and designing novel variants with the expected function.

A Collagen Triple Helix without the Super Helical Twist.

Collagens are ubiquitous in biology functioning as the backbone of the extracellular matrix, forming the primary structural components of key immune system complexes, and fulfilling numerous other structural roles in a variety of systems. Despite this, there is limited understanding of how triple helices, the basic collagen structural units, pack into collagenous assemblies. Here we use a peptide self-assembly system to design collagenous assemblies based on the C1q collagen-like region. Using cryo-EM we solve a structure of one assembly to 3.5 Å resolution and build an atomic model. From this, we identify a triple helix conformation with no superhelical twist, starkly in contrast to the canonical right-handed triple helix. This non-twisting region allows for unique hydroxyproline stacking between adjacent triple helices and also results in the formation of an exposed cavity with rings of hydrophobic amino acids packed symmetrically. We find no precedent for such an arrangement of collagen triple helices and have designed mutant assemblies to probe key stabilizing amino acid interactions in the complex. The mutations behave as predicted by our atomic model. Our findings, combined with the extremely limited experimental structural data on triple helix packing in the literature, suggest that collagen and collagen-like assemblies may adopt a far more varied conformational landscape than previously appreciated. We hypothesize that this is particularly likely adjacent to the termini of these helices and at discontinuities to the required Xaa-Yaa-Gly repeating primary sequence; a discontinuity found in the majority of this class of proteins and in many collagen-associated diseases.

Development and experimental validation of computational methods for human antibody affinity enhancement.

High affinity is crucial for the efficacy and specificity of antibody. Due to involving high-throughput screens, biological experiments for antibody affinity maturation are time-consuming and have a low success rate. Precise computational-assisted antibody design promises to accelerate this process, but there is still a lack of effective computational methods capable of pinpointing beneficial mutations within the complementarity-determining region (CDR) of antibodies. Moreover, random mutations often lead to challenges in antibody expression and immunogenicity. In this study, to enhance the affinity of a human antibody against avian influenza virus, a CDR library was constructed and evolutionary information was acquired through sequence alignment to restrict the mutation positions and types. Concurrently, a statistical potential methodology was developed based on amino acid interactions between antibodies and antigens to calculate potential affinity-enhanced antibodies, which were further subjected to molecular dynamics simulations. Subsequently, experimental validation confirmed that a point mutation enhancing 2.5-fold affinity was obtained from 10 designs, resulting in the antibody affinity of 2nM. A predictive model for antibody-antigen interactions based on the binding interface was also developed, achieving an Area Under the Curve (AUC) of 0.83 and a precision of 0.89 on the test set. Lastly, a novel approach involving combinations of affinity-enhancing mutations and an iterative mutation optimization scheme similar to the Monte Carlo method were proposed. This study presents computational methods that rapidly and accurately enhance antibody affinity, addressing issues related to antibody expression and immunogenicity.

Docking and Structural Modification of Flavonoid Derivative Compounds as Cycloxygenas-2 Enzyme Inhibitors

Seven flavonoid compounds have the activity of inhibiting the cyclooxygenase-2 (COX-2) enzyme, thus providing an anti-inflammatory effect. Molecular docking analysis is needed to determine the binding interaction between flavonoid compounds and the cyclooxygenase-2 (COX-2) enzyme. Objective: This study aims to determine the interaction of flavonoid compounds with the cyclooxygenase-2 (COX-2) enzyme along with the modification of the flavonoid compound structure to increase the binding energy to the cyclooxygenase-2 (COX-2) enzyme. Method: Flavonoid derivative compounds were geometry optimized using VegaZZ software, then target preparation, ligand preparation, docking method validation, and docking analysis were carried out to obtain the interaction between flavonoid compounds and the cyclooxygenase-2 (COX-2) enzyme which is expressed as ∆G and interaction patterns, which include hydrogen bonds, amino acids and functional groups involved, using the program using PyRx-Python 0.8 - AutoDock Vina. Results: The interaction pattern of seven flavonoid derivative compounds with COX-2 enzyme showed hydrogen bonds with amino acids ARG 121, ILE 113, LEU 93, VAL 117. The interaction is similar to the interaction of protoporphrin ix containing co which is the original ligand of the target protein. There is no relationship between the inhibitory activity of flavonoid derivatives and the free energy value of binding (∆G). Modification of the new compound luteolin 7 glucosidase has a better amino acid interaction pattern, namely PRO 155, 154, ARG 44, TYR 131, LEU 153. Conclusions: The binding profile of flavonoid derivatives has the potential to be a candidate for oral cyclooxygenase-2 (COX-2) inhibitor compounds as an anti-inflammatory.

Teaching protein structure and function through molecular visualization.

The function of proteins is governed by their three-dimensional structure. This structure is determined by the chemical characteristics and atomic interactions of amino acids. Students of biochemistry, with a particular focus on protein chemistry, benefit from looking at protein structures and understanding how proteins are built and fold. Due to their three-dimensional nature, static two-dimensional representations in textbooks can be limiting to student learning. Here, we developed a series of tutorials that introduce students to molecular graphics software. The students are challenged to apply the software to look at proteins and to get a deeper understanding of how amino acid properties are linked to structure. We also familiarize students with some of the latest tools in computational structural biology. Students performed the tutorials with visual enthusiasm and reported general satisfaction in being able to visualize theoretical concepts learned during lectures. We further stimulated student engagement by allowing space for self-exploration. We share the tutorial instructions for other teachers to build on them, and we also offer suggestions for further improvement based on student feedback. In summary, we present a series of tutorials aimed at students of an advanced course in protein biochemistry to enable them to explore the universe of protein structures and how those relate to function.

Advances in Cathepsin S Inhibition: Challenges and Breakthroughs in Drug Development.

Cathepsin S (CatS) is a proteolytic enzyme and a member of the cysteine protease family of proteolytic enzymes. Cathepsins S, K, and L are particularly similar in terms of their amino acid sequences and interactions with substrates, and this has made it difficult to develop inhibitors with specificity for either CatS, CatK, or CatL. The involvement of CatS in various disease pathophysiologies (autoimmune disorders, cardiovascular diseases, cancer, etc.) has made it a very important target in drug development. Efforts have been made since the early 1990s to develop a specific CatS inhibitor without any major success. Following many failed efforts to develop an inhibitor for CatS, it was discovered that interactions with the amino acid residues at the S2 and S3 pockets of CatS are critical for the identification of CatS-specific inhibitors. Amino acid residues at these pockets have been the target of recent research focused on developing a non-covalent, reversible, and specific CatS inhibitor. Methods applied in the identification of CatS inhibitors include molecular modeling, in-vitro screening, and in-vivo studies. The molecular modeling process has proven to be very successful in the identification of CatS-specific inhibitors, with R05459072 (Hoffmann-La Roche) and LY3000328 (Eli Lilly Company) which has completed phase 1 clinical trials. CatS inhibitors identified from 2011 to 2023 with promising prospects are discussed in this article.

Structure-Based Virtual Screening and Protein–Protein Docking Analysis of ERBB2 and Associated Proteins for Pediatric Cancer Therapeutic Approaches

Abstract Introduction The Erythroblastosis Oncogene B homolog 2 (ERBB2) protein, also known as human epidermal growth factor receptor 2 (HER2), is a key player in cancer growth, especially in neuroblastoma and gastric cancers. Targeting ERBB2 has led to successful therapies, making it an important focus in cancer research with the potential to improve treatment for HER2-positive cancers. Objective The primary goal of this research is to employ a multifaceted computational approach to identify potential drug candidates targeting ERBB2. We aim to combine virtual screening, protein–protein docking, and functional partner prediction to provide insights into the molecular interactions and potential efficacy of the identified compounds. Additionally, we intend to assess the safety profiles of these compounds using advanced toxicity prediction tools. Methods Relevant protein sequence and structural data for ERBB2 and epidermal growth factor receptor (EGFR) were sourced from publicly available databases. Potential inhibitors from the Enamine and LifeChemicals databases were identified through virtual screening using AutoDock Vina. Functional partners of ERBB2 were explored using STRING, KEGG, and REACTOME servers. The identified compounds were subjected to toxicity prediction using the ProTox-II server. Results Virtual screening led to the selection of 10 compounds with favorable binding energies (–8.346 to –6.296 kcal/mol) and specific amino acid interactions (Thr5, Arg412, Leu414, and Ser441) with the receptor. On the other hand, EGFR was identified as the best functional partner for ERBB2. The EGFR residues Gln408, Lys463, Phe412, and Asp436 found key residues for the complex formation. The toxicity prediction analysis revealed that the majority of compounds exhibited acceptable safety profiles, although a subset of compounds showed lower prediction scores, suggesting the need for further consideration. Conclusion This comprehensive computational approach, integrating virtual screening, protein–protein docking, functional partner identification, and toxicity prediction, offers a systematic framework for efficient drug discovery. The identification of potential lead compounds targeting ERBB2, with emphasis on both binding affinity and safety, underscores the significance of such an approach in streamlining the drug development process. By prioritizing compounds with promising efficacy, functional relevance, and acceptable toxicity profiles, this study advances our understanding of potential therapeutic agents, enhancing the likelihood of successful translation from computational predictions to real-world drug candidates.

Design Glutamate Dehydrogenase for Nonaqueous System by Motifs Reassembly and Interaction Network Analysis.

Glutamate dehydrogenases (GDH) serve as the key regulated enzyme that links protein and carbohydrate metabolism. Combined with motif reassembly and mutation, novel GDHs were designed. Motif reassembly of thermophilic GDH and malate dehydrogenase aims to overcome stability and activity tradeoff in nonaqueous systems. Structural compatibility and dynamic cooperation of the designed AaDHs were studied by molecular dynamics simulation. Furthermore, multipoint mutations improved its catalytic activity for unnatural substrates. Amino acid interaction network analysis indicated that the high density of hydrogen-bonded salt bridges is beneficial to the stability. Finally, the experimental verification determines the kinetics of AaDHs in a nonaqueous system. The activity of Aa05 was increased by 1.78-fold with ionic liquid [EMIM]BF4. This study presents the strategy of a combination of rigid motif assembly and mutations of active sites for robust dehydrogenases with high activity in the nonaqueous system, which overcomes the activity-stability tradeoff effect.

Density and coefficients of Jones–Dole equation for viscosity measurement of l-isoleucine, l-proline, and l-glutamine in aqueous KCl solution at 298.15–323.15 K

The present studies reported the experimental data on thermophysical properties such as density and viscosity of aqueous solutions of different amino acids namely l-isoleucine, l-proline, and l-glutamine in 1.5 mol/L KCl solution at different temperatures ranging from 298.15 to 323.15 K. Hence, the aim of this study is to investigate interactions between amino acids and KCl solution at dilute concentrations. For understanding amino acid and KCl solution interactions, we will investigate ion–ion and ion–solvent interactions. It has been observed that the density and viscosity rise with amino acid concentration and decrease with temperature. Using the Jones–Dole equation, the viscosity A and B coefficients have been determined. The viscosity B-coefficient values for all the three amino acids in aqueous electrolyte system are depicted as positive. The positive values of B-coefficient indicate a strong alignment of the solvent molecules with solute molecules. The amino acid l-glutamine acts as a structure breaker solute. This structure breaking effect of l-glutamine on solvent may be attributed to the domination of hydrophilic nature of amide group. l-isoleucine and l-proline act as structure maker in electrolyte system.

Modification of rice protein and its components: Enhanced fibrils formation and improved foaming properties

Plant-derived proteins like rice protein are considered an ideal source for yielding amyloid fibrils due to sustainability and affordability. However, the inherent low solubility of rice protein often restricts its self-assembly capability under common fibrillization protocols. Hence, this study comprehensively investigated the effect of modification on the self-assembly behavior, protein structure and foaming properties of rice protein and its components. The modification facilitated the transformation of α-helix to β-sheet, promoting fibrils formation. All modified proteins, except rice protein, exhibited significantly increased zeta potential values. AFM results revealed that the modified rice protein and globulin fibrils exhibited entangled aggregation behavior, while the glutelin fibril was notably extended, with several micrometers in length. Additionally, modification promoted the aggregation of albumin and prolamin particles to form short and straight fibrils. Amino acid analysis indicated that the content difference of amino acids with different characteristics and the change of aromatic amino acid interaction caused by modification may lead to different self-assembly behavior of the same protein. Furthermore, the foaming capability and stability of most protein fibrils were significantly improved by the modification. These findings provide valuable insights into the regulation of plant-derived protein fibrillation through modification.

Biased receptor signalling and intracellular trafficking profiles of structurally distinct formylpeptide receptor 2 agonists.

There is increasing interest in developing FPR2 agonists (compound 43, ACT-389949 and BMS-986235) as potential pro-resolving therapeutics, with ACT-389949 and BMS-986235 having entered phase I clinical development. FPR2 activation leads to diverse downstream outputs. ACT-389949 was observed to cause rapid tachyphylaxis, while BMS-986235 and compound 43 induced cardioprotective effects in preclinical models. We aim to characterise the differences in ligand-receptor engagement and downstream signalling and trafficking bias profile. Concentration-response curves to G protein dissociation, β-arrestin recruitment, receptor trafficking and second messenger signalling were generated using FPR2 ligands (BMS-986235, ACT-389949, compound 43 and WKYMVm), in HEK293A cells. Log(τ/KA) was obtained from the operational model for bias analysis using WKYMVm as a reference ligand. Docking of FPR2 ligands into the active FPR2 cryoEM structure (PDBID: 7T6S) was performed using ICM pro software. Bias analysis revealed that WKYMVm and ACT-389949 shared a very similar bias profile. In comparison, BMS-986235 and compound 43 displayed approximately 5- to 50-fold bias away from β-arrestin recruitment and trafficking pathways, while being 35- to 60-fold biased towards cAMP inhibition and pERK1/2. Molecular docking predicted key amino acid interactions at the FPR2 shared between WKYMVm and ACT-389949, but not with BMS-986235 and compound 43. In vitro characterisation demonstrated that WKYMVm and ACT-389949 differ from BMS-986235 and compound 43 in their signalling and protein coupling profile. This observation may be explained by differences in the ligand-receptor interactions. In vitro characterisation provided significant insights into identifying the desired bias profile for FPR2-based pharmacotherapy.

Virtual Screening and Validation of Affinity DNA Functional Ligands for IgG Fc Segment.

The effective attachment of antibodies to the immune sensing interface is a crucial factor that determines the detection performance of immunosensors. Therefore, this study aims to investigate a novel antibody immobilization material with low molecular weight, high stability, and excellent directional immobilization effect. In this study, we employed molecular docking technology based on the ZDOCK algorithm to virtually screen DNA functional ligands (DNAFL) for the Fc segment of antibodies. Through a comprehensive analysis of the key binding sites and contact propensities at the interface between DNAFL and IgG antibody, we have gained valuable insights into the affinity relationship, as well as the principles governing amino acid and nucleotide interactions at this interface. Furthermore, molecular affinity experiments and competitive binding experiments were conducted to validate both the binding ability of DNAFL to IgG antibody and its actual binding site. Through affinity experiments using multi-base sequences, we identified bases that significantly influence antibody-DNAFL binding and successfully obtained DNAFL with an enhanced affinity towards the IgG Fc segment. These findings provide a theoretical foundation for the targeted design of higher-affinity DNAFLs while also presenting a new technical approach for immunosensor preparation with potential applications in biodetection.

Anti-oxidant activity of 1-(1H-imidazo[4,5-c]pyridin-4-yl)ethenone, a Maillard reaction product derived from fructose and histidine.

The Maillard reaction involves the interaction of various amino acids and reducing sugars, resulting in food browning. It often produces appealing aromas and flavors. The complexities of the reaction are such that it can be challenging to identify the often numerous and frequently volatile products formed by it. In the present study, we sought to identify and evaluate an unusual product with anti-oxidant activity arising from a fructose-histidine Maillard reaction model. The anti-oxidant profile of this product was assessed by computational means. The fructose-histidine Maillard reaction products (FH-MRPs) were generated by heating a 2:1 mixture of the sugar and the amino acid at 140 °C for 2 h. Chromatographically separable fractions, labelled DM-1 to DM-8, were obtained using silica gel as the stationary phase and dichloromethane/methanol (DCM/MeOH) mixtures as the mobile one. Fraction DM-5 exhibited the highest 2,2-diphenyl-1-picrylhydrazyl (DPPH) radical scavenging activity, and further bio-assay guided fractionation led to isolation and identification of 1-(1H-imidazo[4,5-c]pyridin-4-yl)ethenone (IMPE) as the active principal, the structure of which was established by nuclear magnetic resonance (NMR) spectroscopic and mass spectral techniques. A mechanism for the formation of IMPE from its precursors is proposed. Density functional theory (DFT) calculations suggest this novel heterocyclic compound exerts its anti-oxidant effects by interacting with DPPH and 2,2'-Azino-bis(3-ethylbenzothiazoline-6-sulfonic acid) (ABTS) radicals. Essentially, IMPE was non-toxic below 300 ug mL-1, showing a concentration-dependent free radical clearance capacity and reducing power within the 100-1000 μg mL-1 range, and moreover, exhibiting significant Fe2+ chelating abilities wihin the 50-200 μg mL-1 range. This study identified the unique FH-MRP, IMPE, and found that it acts as food antioxidant through the chelation of metal ions. © 2024 Society of Chemical Industry.

A Comprehensive Review of The Molecular Dynamic Study Of Chalcones, Coumarins and Chromones as Selective MAO‐B Inhibitors [2015‐Till Date

AbstractMolecular dynamics (MD) simulation is an in silico method used in the biomolecular level of research to study how the protein interacts with the target with time. It provides a detailed information of the protein dynamics and ligand structure with the crucial amino acid interactions. Monoamine oxidase B (MAO−B) is a crucial isoenzyme responsible for the catalyses of oxidative deamination of various biogenic amines in the brain and peripheral tissues. The selective inhibitors of MAO−B are considered as the management of symptoms of neurodegenerative disorders like Alzheimer's disease(AD) and Parkinson disease(PD). Recently the structural scaffolds containing chalcones, coumarins and chromones derived candidates shown potent, selective, competitive and reversible type of MAO−B inhibitors. The structural similarities between the above scaffolds can produce almost similar type of interactions in the inhibitor binding cavity of MAO−B. Numerous molecular simulation reports were supported by the above mentioned fact. The current review focus on the last ten year molecular dynamics report of chalcones, coumarins and chromones towards MAO−B inhibition. The review also focuses on the software details used in the MD dynamics simulation and the structural requirement from each class of compound for the recognition of MAO−B inhibitory activity.

Cryo-EM structure and biochemical analyses of the nucleosome containing the cancer-associated histone H3 mutation E97K.

The Lys mutation of the canonical histone H3.1 Glu97 residue (H3E97K) is found in cancer cells. Previous biochemical analyses revealed that the nucleosome containing the H3E97K mutation is extremely unstable as compared to the wild-type nucleosome. However, the mechanism by which the H3E97K mutation causes nucleosome instability has not been clarified yet. In the present study, the cryo-electron microscopy structure of the nucleosome containing the H3E97K mutation revealed that the entry/exit DNA regions of the H3E97K nucleosome are disordered, probably by detachment of the nucleosomal DNA from the H3 N-terminal regions. This may change the intra-molecular amino acid interactions with the replaced H3 Lys97 residue, inducing structural distortion around the mutated position in the nucleosome. Consistent with the nucleosomal DNA end flexibility and the nucleosome instability, the H3E97K mutation exhibited reduced binding of linker histone H1 to the nucleosome, defective activation of PRC2 (the essential methyltransferase for facultative heterochromatin formation) with a poly-nucleosome, and enhanced nucleosome transcription by RNA polymerase II.

Synthesis and Structure of Novel Phenothiazine Derivatives, and Compound Prioritization via In Silico Target Search and Screening for Cytotoxic and Cholinesterase Modulatory Activities in Liver Cancer Cells and In Vivo in Zebrafish.

Phenothiazines (PTZ) are antipsychotics known to modulate a variety of neurotransmitter activities that include dopaminergic and cholinergic signaling and have been identified as potential anticancer agents in vitro. However, it is important to also test whether a highly cytotoxic, repurposed, or novel PTZ has low toxicity and neuromodulatory activity in vivo using vertebrate model organisms, such as zebrafish. In this study, we synthesized novel phenothiazines and screened them in vitro in liver cancer and in vivo in zebrafish embryos/larvae. The syntheses of several intermediate PTZ 10-yl acyl chlorides were followed by elemental analysis and determination of 1H NMR and 13C NMR mass (ESI+) spectra of a large number of novel PTZ 10-carboxamides. Cytotoxicities of 28 PTZ derivatives (1-28) screened against Hep3B and SkHep1 liver cancer cell lines revealed five intermediate and five novel leads along with trifluoperazine (TFP), prochlorperazine (PCP), and perphenazine, which are relatively more cytotoxic than the basic PTZ core. Overall, the derivatives were more cytotoxic to Hep3B than SkHep1 cells. Moreover, in silico target screening identified cholinesterases as some of the commonest targets of the screened phenothiazines. Interestingly, molecular docking studies with acetylcholinesterase (AChE) and butyrylcholinesterase proteins showed that the most cytotoxic compounds 1, 3, PCP, and TFP behaved similar to Huprin W in their amino acid interactions with the AChE protein. The highly cytotoxic intermediate PTZ derivative 1 exhibited a relatively lower toxicity profile than those of 2 and 3 during the zebrafish development. It also modulated in vivo the cholinesterase activity in a dose-dependent manner while significantly increasing the total cholinesterase activity and/or ACHE mRNA levels, independent of the liver cancer cell type. Our screen also identified novel phenothiazines, i.e., 8 and 10, with significant cytotoxic and cholinesterase modulatory effects in liver cancer cells; yet both compounds had low levels of toxicity in zebrafish. Moreover, they modulated the cholinesterase activity or expression of ACHE in a cancer cell line-specific manner, and compound 10 significantly inhibited the cholinesterase activity in zebrafish. Accordingly, using a successful combination of in silico, in vitro, and in vivo approaches, we identified several lead anticancer and cholinesterase modulatory PTZ derivatives for future research.

Synthesis and In-silico Docking Analysis of 2-Phenylindolizine Acetamide Scaffolds: Potent Anticancer and Antibacterial Ta

Background: Although several specialized methods for treating various cancers have been developed, clinical outcomes for patients with colon cancer have shown unfavorable effects in addition to chemotherapeutic drug resistance. Therefore, finding medicinal substances with minimal to no side effects is crucial in the fight against cancer. Further, this study underscores the significance of 2-phenylindolizine acetamide due to the diverse biological features and the extensive application of this moiety as an effective anticancer and antibacterial drug. Objective: The goal of the study was to investigate novel, prospective 2-phenylindolizines as anticancer and antibacterial drugs. Methods: The synthesized compounds were characterized by different spectral analyses like 1 H NMR, 13C NMR, IR, and mass spectrometry. Pharmacokinetics in-silico studies were performed to predict the drug performance in the body using the SwissADME kit. The molecular docking was performed to check the catalytic binding site between the Topoisomerase-IV from S. pneumoniae and synthesized compounds. The antibacterial activity was assessed using the agar well diffusion method, and the compounds were screened for in vitro anticancer activity using an MTT assay with doxorubicin as a reference. Results: Interestingly, 2-phenylindolizine scaffolds 7c, 7f, and 7g revealed a remarkable antibacterial activity against relevant organisms S. aureus, E. coli, S. pneumoniae, and P. aeruginosa. The target compounds 7e and 7h showed excellent anticancer activity against Colo-205 and MDA-MB-231 cell lines with IC50 values of 68.62, 62.91, 54.23, and 46.34 µM, respectively. Compounds 7a, 7f, and 7c exhibited the highest hydrogen bonding amino acid interactions Asp83 (2.23 Å), Asp83 (2.08 Å), His74 (2.05 Å), His76 (1.71 Å), and Ser80 (1.05 Å) with active site of Topoisomerase-IV from S. pneumoniae (4KPE). Conclusion: This research focused on recent advances in drug design and development, as well as Phenylindolizine derivatives and how they work on anticancer and antibacterial sites of action.