Drug Design Studies Research Articles

Pharmacological Potential of Sulindac and Its Active Metabolite: A Comprehensive Review

: In this review, we describe and discuss the pharmaceutical aspects, pharmacokinetic profile, and preclinical and clinical studies of sulindac and its active metabolite and emphasise their potential activity not only in anti-inflammation strategies but also as chemoprevention drug candidates. Though they are widely validated through in vitro and in vivo models, to date, no efforts have been made to compile in a single review on their pharmacologically potential, pharmacokinetics and toxicity profiles. Key databases such as PubMed, Science Direct, Scopus, and Google Scholar, among others, were probed for a systematic search using keywords to retrieve relevant publications. An exhaustive electronic survey of the related literature on the pharmacologically potential activity and the pharmacokinetic and toxicity profiles of sulindac resulted in around 200 articles (1975 and 2023) being included. The studies conducted on sulindac sulphide and sulindac sulfone metabolites reported a varied range of biological effects deployed in this review. The review concluded that there is scope for repurposing sulindac using computer-aided drug design and biological study to find out possible new targets for strengthening the potency and selectivity of the metabolites.

Exploring the orphan immune receptor TREM2 and its non-protein ligands: In silico characterization

The triggering receptor expressed on myeloid cells 2 (TREM2) is an immunoreceptor that interacts with a wide range of non-protein ligands, and it has been implicated in infectious and non-infectious diseases. However, there is a limited understanding on how this receptor interacts with non-protein ligands and the potential of such information to develop new therapeutic drugs. Therefore, our study aimed to elucidate the interactions between TREM2 and its non-protein ligands. First, we searched PubChem and Protein Data Bank (PDB) for TREM2 structures and their corresponding non-protein ligands. Subsequently, these structures were employed in molecular docking and MM/GBSA simulations with the Maestro software and molecular dynamics in GROMACS software. TREM2 was subsequently subjected to druggable site prediction using CavityPlus and receptor-based drug repositioning via the DrugRep server. TREM2 interacts with high affinity with its 12 non-protein ligands, with affinity values ranging from −33.01 kcal/mol for phosphatidylserine to −80.87 kcal/mol for cardiolipin (CLP). In molecular dynamics simulations, homodimeric TREM2 bound more stably to its lipid ligands, such as CLP and PSF, whereas it was unstable when unbound. The interactions between the receptor and its non-protein ligands were driven by the complementarity determining regions (CDR) 1 and 2, that are present in the hydrophobic and positively charged regions, highlighting that the Y38–R98 region is fundamental for drugs targeting TREM2. Our data underscore the significance of TREM2's CDRs in recognizing its ligands, suggesting they as promising targets for prospective drug design studies.

Graph masked self-distillation learning for prediction of mutation impact on protein–protein interactions

Assessing mutation impact on the binding affinity change (ΔΔG) of protein–protein interactions (PPIs) plays a crucial role in unraveling structural-functional intricacies of proteins and developing innovative protein designs. In this study, we present a deep learning framework, PIANO, for improved prediction of ΔΔG in PPIs. The PIANO framework leverages a graph masked self-distillation scheme for protein structural geometric representation pre-training, which effectively captures the structural context representations surrounding mutation sites, and makes predictions using a multi-branch network consisting of multiple encoders for amino acids, atoms, and protein sequences. Extensive experiments demonstrated its superior prediction performance and the capability of pre-trained encoder in capturing meaningful representations. Compared to previous methods, PIANO can be widely applied on both holo complex structures and apo monomer structures. Moreover, we illustrated the practical applicability of PIANO in highlighting pathogenic mutations and crucial proteins, and distinguishing de novo mutations in disease cases and controls in PPI systems. Overall, PIANO offers a powerful deep learning tool, which may provide valuable insights into the study of drug design, therapeutic intervention, and protein engineering.

Inhibition Effects of Some Non-Proteinogenic Amino Acid Derivatives on Carbonic Anhydrase Isoenzymes and Acetylcholinesterase: An In Vitro Inhibition and Molecular Modeling Studies.

Amino acid derivatives are molecules of interest for medicinal chemistry and drug design studies due to their important chemical properties. In this study, the inhibition effects of some non-proteinogenic amino acid derivatives (hippuric acid (A), N-(9-Fluorenylmethoxycarbonyl)-D-valine (B), N-Z-(1-Benzotriazolylcarbonyl) methylamine (C), (S)-N-Z-1-Benzotriazolylcarbonyl-2-phenylethylamine (D)) on carbonic anhydrase I (hCA-I), II (hCA-II) isoenzymes and acetylcholinesterase (AChE) activity, whose inhibitors are of vital pharmacological importance, were examined. While carbonic anhydrase (CA) inhibitors are effective molecule candidates for the treatment of many diseases from glaucoma to cancer, acetylcholinesterase inhibitors are target molecules for the treatment of Alzheimer's disease. According to the results of this study, compound D had a strong inhibitory effect on hCA-I (IC50: 0.836 μM) and hCA-II (IC50: 0.661 μM), while compound B (IC50: 100 μM) showed a strong inhibitory effect on AChE activity. In addition, inhibition results were supported by molecular modeling studies. We hope that the obtained results will contribute to the synthesis of new and effective amino acid derivative inhibitors for CA and AChE.

In-Silico ADMET Prediction, Structure-Based Drug Design and Molecular Docking Studies of Quinazoline Derivatives as Novel EGFR Inhibitors

This Present research provides valuable insights and implications for the development of quinazoline derivatives as novel EGFR inhibitors. The in-silico ADMET predictions indicate that the quinazoline derivatives possess promising drug-like properties, suggesting their potential for further development as oral drugs. The low risk of toxicity and favorable metabolic and excretion profiles enhance their suitability for therapeutic applications Molecular docking studies revealed strong binding interactions between the quinazoline derivatives and the EGFR kinase domain. These interactions suggest that these compound shave the potential to effectively inhibit EGFR activity, making them promising candidates for anti- cancer drug development to progress from in-silico findings to clinical applications, further research is essential. Future work should encompass in vitro and in vivo experiments to validate the inhibitory potential of these compounds against EGFR. Additionally, pharmacokinetic studies are warranted to confirm their ADMET properties. Structural optimization through medicinal chemistry approaches may further enhance their binding affinities and specificity for EGFR. It represents a pivotal step in the exploration of quinazoline derivatives as novel EGFR inhibitors. The combined efforts in ADMET prediction, structure-based drug design, and molecular docking have provided a strong foundation for the development of innovative anti-cancer therapies. The potential of these compounds to target EGFR, a crucial player in various cancers, holds great promise for improving the treatment options available to patients and advancing the field of oncology.

Investigating the binding affinity, molecular dynamics, and ADMET properties of curcumin-IONPs as a mucoadhesive bioavailable oral treatment for iron deficiency anemia

Iron deficiency anemia (IDA) is a common health issue, and researchers are interested in overcoming it. Nanotechnology green synthesis is one of the recent approaches to making efficient drugs. In this study, we modeled curcumin-coated iron oxide nanoparticles (cur-IONPs) to study their predicted toxicity and drug-likeness properties, then to investigate mucoadhesive behavior by docking cur-IONPs with two main mucin proteins in gastrointestinal tract (GIT) mucosa (muc 5AC and muc 2). Furthermore, the stability of cur-IONPs/protein complexes was assessed by molecular dynamics. Our in-silico studies results showed that cur-IONPs were predicted to be potential candidates to treat IDA due to its mucoadhesive properties, which could enhance the bioavailability, time residency, and iron absorbance through GIT, in addition to its high safety profile with high drug-likeness properties and oral bioavailability. Finally, molecular dynamic simulation studies revealed stable complexes supporting strength docking studies. Our results focus on the high importance of in-silico drug design studies; however, they need to be supported with in vitro and in vivo studies to reveal the efficacy, toxicity, and bioavailability of cur-IONPs.

Synthesis of Flavonoid/Sulfonamide Hybrid Molecules as Potential Inhibitors of Cholinesterases: In Vitro, Molecular Docking, Molecular Dynamic and DFT Studies

AbstractAcetylcholinesterase (AChE) and butyrylcholinesterase (BChE) belong to the serine hydrolase enzyme family and has been implicated to have a crucial role in the pathogenesis of Alzheimer's disease (AD). Generally, treatment strategies for AD has focused on the development of inhibitors of these enzymes. In light of this, a series of novel N‐(4‐sulfamoylphenyl)‐3‐methylflavone‐8‐carboxamide compounds were synthesized and their inhibition potentials on AChE and BChE were investigated. The results of the inhibition assay revealed that N‐(2,6‐dichloro‐4‐sulfamoylphenyl)‐3‐methylflavone‐8‐carboxamide was the most active inhibitor for AChE and BChE with Ki values of 4.2 nM and 0.15 μM, respectively. Compared to the standard drug rivastigmine all the synthesized compounds showed better AChE inhibition properties, while the BChE inhibition was comparable to the drug. The results indicate that N‐(2,6‐dichloro‐4‐sulfamoylphenyl)‐3‐methylflavone‐8‐carboxamide can be considered for further drug design studies and thus DFT analyses were conducted to clarify the electronic structures of the compound while molecular docking was performed to determine the binding affinities of the compound to target proteins. Lastly, molecular dynamics (MD) simulations were conducted to assess the time‐dependent behavioral changes of the complexes.

Diet-induced Obesity: Pathophysiology, Consequences and Target Specific Therapeutic Strategies.

Diet has emerged as a pivotal factor in the current time for diet-induced obesity (DIO). A diet overloaded with fats and carbohydrates and unhealthy dietary habits contribute to the development of DIO through several mechanisms. The prominent ones include the transition of normal gut microbiota to obese microbiota, under-expression of AMPK, and abnormally high levels of adipogenesis. DIO is the root of many diseases. The present review deals with various aspects of DIO and its target proteins that can be specifically used for its treatment. Also, the currently available treatment strategies have been explored. It was found that the expression of five proteins, namely, PPARγ, FTO, CDK4, 14-3-3 ζ protein, and Galectin-1, is upregulated in DIO. They can be used as potential targets for drug-designing studies. Thus, with these targets, the treatment strategy for DIO using natural bioactive compounds can be a safer alternative to medications and bariatric surgeries.

Comparative study of Sombor index and its various versions using regression models for top priority polycyclic aromatic hydrocarbons

The aromatic compounds having structural configurations with two or more fused benzene rings are the polycyclic aromatic hydrocarbons (PAHs). Topological indices are valuable tools for studying the structure property relationships of PAHs and also helps in predicting various properties and activities. They find applications widely in computational chemistry, drug design and QSPR studies. This article focuses on analysing the potential predictive index for Sombor index (SO), elliptic Sombor index (ESO), Euler Sombor index (EU), reverse Sombor index (RSO), reverse elliptic Sombor index (RESO) and reverse Euler Sombor index (REU) using regression models for top priority 38 PAHs. From the study it is evident that, SO and RSO have proved to be potential predictive indices among the considered degree-based and reverse degree-based indices. The variation of best predictive index with minimal RMSE are plotted for linear, quadratic and cubic regression models for better understanding.

PGAT-ABPp: harnessing protein language models and graph attention networks for antibacterial peptide identification with remarkable accuracy.

The emergence of drug-resistant pathogens represents a formidable challenge to global health. Using computational methods to identify the antibacterial peptides (ABPs), an alternative antimicrobial agent, has demonstrated advantages in further drug design studies. Most of the current approaches, however, rely on handcrafted features and underutilize structural information, which may affect prediction performance. To present an ultra-accurate model for ABP identification, we propose a novel deep learning approach, PGAT-ABPp. PGAT-ABPp leverages structures predicted by AlphaFold2 and a pretrained protein language model, ProtT5-XL-U50 (ProtT5), to construct graphs. Then the graph attention network (GAT) is adopted to learn global discriminative features from the graphs. PGAT-ABPp outperforms the other fourteen state-of-the-art models in terms of accuracy, F1-score and Matthews Correlation Coefficient on the independent test dataset. The results show that ProtT5 has significant advantages in the identification of ABPs and the introduction of spatial information further improves the prediction performance of the model. The interpretability analysis of key residues in known active ABPs further underscores the superiority of PGAT-ABPp. The datasets and source codes for the PGAT-ABPp model are available at https://github.com/moonseter/PGAT-ABPp/.

Dynamic interchange between two protonation states is characteristic of active sites of cholinesterases.

Cholinesterases are well-known and widely studied enzymes crucial to human health and involved in neurology, Alzheimer's, and lipid metabolism. The protonation pattern of active sites of cholinesterases influences all the chemical processes within, including reaction, covalent inhibition by nerve agents, and reactivation. Despite its significance, our comprehension of the fine structure of cholinesterases remains limited. In this study, we employed enhanced-sampling quantum-mechanical/molecular-mechanical calculations to show that cholinesterases predominantly operate as dynamic mixtures of two protonation states. The proton transfer between two non-catalytic glutamate residues follows the Grotthuss mechanism facilitated by a mediator water molecule. We show that this uncovered complexity of active sites presents a challenge for classical molecular dynamics simulations and calls for special treatment. The calculated proton transfer barrier of 1.65 kcal/mol initiates a discussion on the potential existence of two coupled low-barrier hydrogen bonds in the inhibited form of butyrylcholinesterase. These findings expand our understanding of structural features expressed by highly evolved enzymes and guide future advances in cholinesterase-related protein and drug design studies.

Structure and Activity of Reconstructed Pseudo-Ancestral Cyclotides.

Cyclotides are cyclic peptides that are promising scaffolds for the design of drug candidates and chemical tools. However, despite there being hundreds of reported cyclotides, drug design studies have commonly focussed on a select few prototypic examples. Here, we explored whether ancestral sequence reconstruction could be used to generate new cyclotides for further optimization. We show that the reconstructed 'pseudo-ancestral' sequences, named Ancy-m (for the ancestral cyclotide of the Möbius sub-family) and Ancy-b (for the bracelet sub-family), have well-defined structures like their extant members, comprising the core structural feature of a cyclic cystine knot. This motif underpins efforts to re-engineer cyclotides for agrochemical and therapeutic applications. We further show that the reconstructed sequences are resistant to temperatures approaching boiling, bind to phosphatidyl-ethanolamine lipid bilayers at micromolar affinity, and inhibit the growth of insect cells at inhibitory concentrations in the micromolar range. Interestingly, the Ancy-b cyclotide had a higher oxidative folding yield than its comparator cyclotide cyO2, which belongs to the bracelet cyclotide subfamily known to be notoriously difficult to fold. Overall, this study provides new cyclotide sequences not yet found naturally that could be valuable starting points for the understanding of cyclotide evolution and for further optimization as drug leads.

In-silico analysis of ribosome inactivating protein (RIP) of the Cucurbitaceae family.

Ribosome-inactivating proteins (RIPs) are highly active N-glycosidases that depurinate both bacterial and eukaryotic rRNAs, halting protein synthesis during translation. Found in a diverse spectrum of plant species and tissues, RIPs possess antifungal, antibacterial, antiviral, and insecticidal properties linked to plant defense. In this study, we investigated the physiochemical properties of RIP peptides from the Cucurbitaceae family through bioinformatics approaches. Molecular weight, isoelectric point, aliphatic index, extinction coefficient, and secondary structures were analyzed, revealing their hydrophobic nature. The novelty of this work lies in the comprehensive examination of RIPs from the Cucurbitaceae family and their potential therapeutic applications. The study also elucidated the binding interactions of Cucurbitaceae RIPs with key biological targets, including Interleukin-6 (IL-6). Strong hydrogen bond interactions between RIPs and these targets suggest potential for innovative insilico drug design and therapeutic applications, particularly in cancer treatment. Comprehensive analysis of bond lengths using Ligpolt + software provides insights for optimizing molecular interactions, offering a valuable tool for drug design and structural biology studies.

Prediction of 3D RNA Structures from Sequence Using Energy Landscapes of RNA Dimers: Application to RNA Tetraloops.

Access to the three-dimensional structure of RNA enables an ability to gain a more profound understanding of its biological mechanisms, as well as the ability to design RNA-targeting drugs, which can take advantage of the unique chemical environment imposed by a folded RNA structure. Due to the dynamic and structurally complex properties of RNA, both experimental and traditional computational methods have difficulty in determining RNA's 3D structure. Herein, we introduce TAPERSS (Theoretical Analyses, Prediction, and Evaluation of RNA Structures from Sequence), a physics-based fragment assembly method for predicting 3D RNA structures from sequence. Using a fragment library created using discrete path sampling calculations of RNA dinucleoside monophosphates, TAPERSS can sample the physics-based energy landscapes of any RNA sequence with relatively low computational complexity. We have benchmarked TAPERSS on 21 RNA tetraloops, using a combinatorial algorithm as a proof-of-concept. We show that TAPERSS was successfully able to predict the apo-state structures of all 21 RNA hairpins, with 16 of those structures also having low predicted energies as well. We demonstrate that TAPERSS performs most accurately on GNRA-like tetraloops with mostly stacked loop-nucleotides, while having limited success with more dynamic UNCG and CUYG tetraloops, most likely due to the influence of the RNA force field used to create the fragment library. Moreover, we show that TAPERSS can successfully predict the majority of the experimental non-apo states, highlighting its potential in anticipating biologically significant yet unobserved states. This holds great promise for future applications in drug design and related studies. With discussed improvements and implementation of more efficient sampling algorithms, we believe TAPERSS may serve as a useful tool for a physics-based conformational sampling of large RNA structures.

Imidazole-Derived Alkyl and Aryl Ethers: Synthesis, Characterization, In Vitro Anticancer and Antioxidant Activities, Carbonic Anhydrase I-II Inhibition Properties, and In Silico Studies.

Imidazole derivatives display extensive applications in pharmaceutical chemistry and have been investigated as bioactive compounds for medicinal chemistry. In this study, besides the starting materials (3a-c and 4a-c), synthesis, characterization, and biological activity studies were conducted on a total of 18 compounds, nine of which are known and the other nine are original. The compounds investigated in the study are a series of alkyl (7-15) and aryl (16-24) ether derivatives bearing substituted phenyl and imidazole rings, which were characterized using various methods including 1H NMR, 13C NMR, FT-IR analysis, elemental analysis, and mass spectroscopy. Computer-aided drug design studies have been carried out to predict the biological activities of compounds. Besides DFT calculations, the binding affinities of the compounds to EGFR, VEGFR2, FGFR1, HSP90, hCA I, and hCA II were investigated. Additionally, drug-likeness and ADME analyses were performed on the compounds. Anticancer, antioxidant, and enzyme inhibition activity tests were performed in biological activity studies on the synthesized compounds. Among the synthesized compounds, compounds 17 and 19-24 generally exhibited inhibition profiles against the widespread cytosolic hCA I isozyme with IC50 values ranging from 4.13 to 15.67 nM and cytosolic hCA II isozyme with IC50 values ranging from 5.65 to 14.84 nM. L929 (mouse fibroblast cell line) was used as the control healthy cell line, and MCF7 (breast cancer), C6 (rat glioblastoma), and HT-29 (colon cancer) cells were used in cell culture studies as cancer cell lines. Before the study on cancer cells, all compounds were examined on healthy cells, and their cytotoxicity was determined. As a result of these data, studies continued with six compounds determined to be nontoxic. On cancerous cells, it was determined that compounds 3a, 3b, 4a, 4b, 4c, and 7 had cytotoxic effects on both colon cancer and brain tumors. It was found that compound 3b had a more toxic effect than cisplatin on the glioma cell line with an IC50 value of 10.721 ± 0.38 μM, and compound 3a had a more toxic effect on the colon cancer cell line with an IC50 value of 20.88 ± 1.02 μM. However, it was determined that the same compounds did not have a statistically significant effect on breast cancer. Flow cytometry studies also showed that when the IC50 dose of compound 3b was applied to the C6 cell line, the cells tended to early and late apoptosis. Additionally, it has been shown by flow cytometry that the cell cycle stops in the G0/G1 phase. A similar effect was observed in the colon cancer cell line with compound 3a. Compound 3b caused early and late apoptosis of the colon cancer cell line with the applied IC50 dose and stopped the cell cycle in the G0/G1 phase. Finally, the FRAP method studied all synthesized compounds' antioxidant effects. According to the measured antioxidant power results, it was determined that no compound had a more effective reducing power than vitamin E.

Computer-Assisted Drug Discovery of Potential African Anti-SARS-CoV-2 Natural Products Targeting the Helicase Protein

Objectives: In our continuous efforts to combat COVID-19, our objective was to conduct a comprehensive computer-aided drug design study utilizing 4924 African natural metabolites sourced from diverse databases across various African regions from 1962 to 2019. The primary goal was to target the SARS-CoV-2 helicase, a crucial enzyme in viral replication. Methods: We employed structural fingerprint and molecular similarity studies with VXG, the co-crystallized ligand, as a reference. Subsequently, docking and absorption, distribution, metabolism, excretion, and toxicity (ADMET) studies were conducted. Results: The structural fingerprint analysis identified 200 structurally similar compounds, then the molecular similarity studies selected 40 compounds. Among them, 15 metabolites with low free energies, favorable binding modes, and promising ADMET properties were identified. Four compounds were excluded according to the toxicity studies. Compound 1552, 1-(( S)-2,3-dihydro-2-(( R)-1-hydroxypropan-2-yl)benzofuran-5-yl)ethenone, exhibited the most favorable docking results. Molecular dynamics simulations conclusively demonstrated its stable binding to the SARS-CoV-2 helicase, characterized by low energy and optimal dynamics. Conclusion: The findings suggest promising avenues for potential COVID-19 cures, encouraging further exploration through in vitro and in vivo studies of the identified compounds, particularly compound 1552.

Thymoquinone: A novel treatment option for triple negative breast cancer

The most common treatment modes of cancer include chemotherapies along with other modes of treatment. But often resistance is developed and gruels towards the discovery of new modes of treatment for cancer. Natural products are used for ages in the treatment. One such component is thymoquinone (TQ). It has been extensively studied against cancer, especially in treating breast cancer. The review article updates its status on research against breast cancer and triple negative breast cancer. The paper describes various breast cancer (BC) treatment options in combination with TQ or alone such as heat shock 70-kDa protein 6 (HSPA6) situated on human chromosome in inhibition of BC growth, MMP-9 and MMP-2 as biomarkers in BC, use of cancer stem cells in vascular formation in solid tumor by VM (vascular mimicry) via MMP-2 and MT1-MMP genes upregulation, use of exosomes extracted from adipocyte-derived mesenchymal stem cells, cancer immunotherapy or immuno-oncology where natural killer lymphocyte cells are used to enhance innate immune response against tumors and pathogens, use of (TRAIL) tumor necrosis factor-related apoptosis-inducing ligand agonists, drugs with synergistic activity, identifying targeted genes IL17RD, and diet having natural molecules that can act potentially against cancer. The article also updates on research associated with TQ in overcoming hindrances related to its poor bioavailability making it an effective clinically acting drug molecule. Recent research indicates that TQ can be a successful candidate to eradicate cancer through its clinical interventions followed by drug design studies.

AHoJ-DB: A PDB-wide Assignment of apo & holo Relationships Based on Individual Protein–Ligand Interactions

A single protein structure is rarely sufficient to capture the conformational variability of a protein. Both bound and unbound (holo and apo) forms of a protein are essential for understanding its geometry and making meaningful comparisons. Nevertheless, docking or drug design studies often still consider only single protein structures in their holo form, which are for the most part rigid. With the recent explosion in the field of structural biology, large, curated datasets are urgently needed. Here, we use a previously developed application (AHoJ) to perform a comprehensive search for apo-holo pairs for 468,293 biologically relevant protein–ligand interactions across 27,983 proteins. In each search, the binding pocket is captured and mapped across existing structures within the same UniProt, and the mapped pockets are annotated as apo or holo, based on the presence or absence of ligands. We assemble the results into a database, AHoJ-DB (www.apoholo.cz/db), that captures the variability of proteins with identical sequences, thereby exposing the agents responsible for the observed differences in geometry. We report several metrics for each annotated pocket, and we also include binding pockets that form at the interface of multiple chains. Analysis of the database shows that about 24% of the binding sites occur at the interface of two or more chains and that less than 50% of the total binding sites processed have an apo form in the PDB. These results can be used to train and evaluate predictors, discover potentially druggable proteins, and reveal protein- and ligand-specific relationships that were previously obscured by intermittent or partial data.Availability: www.apoholo.cz/db

1,3,5-triazine derivatives as potential anticancer agents against lung and breast cancer cell lines: Synthesis, biological evaluation, and structure-based drug design studies

Morpholine substituted 1,3,5-triazines have been recently recognized as potent inhibitors of PI3K-mTOR kinase signalling pathway. In this paper, we have performed synthesis and in vitro anti-cancer activity of trisubstituted 1,3,5-triazine derivatives against the A549 (Lung cancer) and MCF-7 (Breast cancer) cell lines. All synthesized analogs showed good inhibitory activity against both cell lines. Out of ten compounds, only two compounds, benzyl-4-(4-(4-(4-fluorophenyl)piperazin-1-yl)-6-morpholino-1,3,5-triazin-2-yl)piperazine-1-carboxylate (Compound 6b), shows 9.61 µM anticancer activity against A549 cell line and 22.68 µM activity against MCF-7 cell lines. Similarly, benzyl-4-(4-morpholino-6-thiomorpholino-1,3,5-triazin-2-yl)piperazine-1-carboxylate (Compound 6c) shows 39.70 µM anticancer activity against A549 cell line and 12.88 µM activity against MCF-7 cell lines. It shows that compound 6b is a potent inhibitor for A549 lung cancer cell line, and compound 6c shows excellent inhibitory activity for MCF-7 breast cancer cell line (9.16 µM and 12.88 µM, respectively). Both compounds (Compound 6b and Compound 6c) did not show toxicity to the non-cancerous HaCaT (Immortalized human keratinocytes) cells. Additionally, molecular descriptors of all synthesized compounds (6a-j) were calculated. After in vitro studies, the potent compounds 6b and 6c were validated using molecular docking and dynamics simulation studies and informed their binding affinities and conformational stability in the binding cavity. Structure-based drug design approach was followed for designing compounds based on potential ligand-receptor interaction. The result shows that triazine analogs serve as lead structures for generating new anti-cancer drugs.

Comparative Analysis of Leishmania major Nucleoside Hydrolases Toward Selecting Multi-target Strategy.

Leishmania causes multiple types of leishmaniasis in different parts of the world. It has a lack of metabolic machine to produce purine bases. Therefore, the parasite produces purine bases through the breakdown of nutritional nucleotides and it makes the nucleoside hydrolases (NHs) good drug targets. They have different substrate-preferring (SP) types. Our objectives were modeling and comparative analysis of these protein structures for Leishmania major. In this work, available sequences for all SP types of L. major NH enzymes including inosine-uridine preferring NH (IUNH), inosine-guanosine preferring NH (IGNH), and inosine-adenosine-guanosine preferring NH (IAGNH) were used to make 24 structural models via SWISS-MODEL and LOMETS. After evaluating the structural models, three enzyme structures were finalized and used to analyze substrate-binding pockets. The three SP types of L. major NH enzymes that can breakdown purine nucleosides were highly different in terms of sequence, structure, and profile of interacting residues within the substrate-binding pockets. In this study, new enzyme structures have been presented for three SP types and they have been compared in different aspects and it indicated that they were very different from each other. Although, previously indicated that from these three SP types in genera other than Leishmania, the role of IGNH and IAGNH was greater than IUNH in supplying purine bases, till this work, just IUNH has been structurally studied and used in drug-design investigations for Leishmania. Therefore, we are offering to use all three SP types of NHs as multi-target strategy in anti-leishmaniosis drug-design studies.