Quantitative structure-activity relationship and ADME prediction studies on series of spirooxindoles derivatives for anti-cancer activity against colon cancer cell line HCT-116.

Forty-one derivatives of spirooxindoles, active against HCT-116 colon cancer cells, underwent pharmacophore-based 3D-QSAR analysis to understand their correlation with anti-cancer activity. The study identified a seven-point pharmacophore model (ADHHRRR1) and QSAR models, offering insights for lead optimization and novel analogue design, thus advancing anti-cancer drug discovery. This research underscores the value of molecular modeling in elucidating structure-activity relationships and enhancing drug development efforts.

Design, Synthesis, and Biological Evaluation of Quinoline (Quinolinone) Derivatives as NADPH Oxidase (NOX) Inhibitors.

NADPH oxidases (NOXs) are the sole enzyme in the human body that can directly produce reactive oxygen species. Recent studies have shown that NOXs is a very promising target for the treatment of diabetic nephropathy (DN). Here, a series of quinoline(quinolinone) derivatives have been designed based on pharmacophore strategy, synthesized and evaluated. Among them, 19d exhibits potent antiproliferative and NOXs inhibitory activities, and is worthy for further investigation.

Structure-based pharmacophore modeling for precision inhibition of mutant ESR2 in breast cancer: A systematic computational approach.

BACKGROUND: Breast cancer, a leading cause of female mortality, is closely linked to mutations in estrogen receptor beta (ESR2), particularly in the ligand-binding domain, which contributed to altered signaling pathways and uncontrolled cell growth. OBJECTIVES/AIMS: This study investigates the molecular and structural aspects of ESR2 mutant proteins to identify shared pharmacophoric regions of ESR2 mutant proteins and potential therapeutic targets aligned within the pharmacophore model. METHODS: This study was initiated by establishing a common pharmacophore model among three mutant ESR2 proteins (PDB ID: 2FSZ, 7XVZ, and 7XWR). The generated shared feature pharmacophore (SFP) includes four primary binding interactions: Hydrogen bond donors (HBD), hydrogen bond acceptors (HBA), hydrophobic interactions (HPho), and Aromatic interactions (Ar), along with halogen bond donors (XBD) and totalling 11 features (HBD: 2, HBA: 3, HPho: 3, Ar: 2, XBD: 1). By employing an in-house Python script, these 11 features distributed into 336 combinations, which were used as query to isolate a drug library of 41,248 compounds and subjected to virtual screening through the generated SFP. RESULTS: The virtual screening demonstrated 33 hits showing potential pharmacophoric fit scores and low RMSD value. The top four compounds: ZINC94272748, ZINC79046938, ZINC05925939, and ZINC59928516 showed a fit score of more than 86% and satisfied the Lipinski rule of five. These four compounds and a control underwent molecular (XP Glide mode) docking analysis against wild-type ESR2 protein (PDB ID: 1QKM), resulting in binding affinity of -8.26, -5.73, -10.80, and -8.42 kcal/mol, respectively, along with the control -7.2 kcal/mol. Furthermore, the stability of the selected candidates was determined through molecular dynamics (MD) simulations of 200 ns and MM-GBSA analysis. CONCLUSION: Based on MD simulations and MM-GBSA analysis, our study identified ZINC05925939 as a promising ESR2 inhibitor among the top four hits. However, it is essential to conduct further wet lab evaluation to assess its efficacy.

Molecular Regulator Driving Endometriosis Towards Endometrial Cancer: A Multi-Scale Computational Investigation to Repurpose Anti-Cancer drugs.

Endometriosis is a gynecological disorder among reproductive-aged women. Recent epidemiological investigations suggest endometriosis increases the risk of endometrial cancer. However, the molecular entity leading to endometriosis-to-endometrial cancer is largely unknown. This study aimed to combine a variety of computational approaches to identify the key therapeutic target promoting endometriosis-to-endometrial cancer and screen potential inhibitors against target to prevent cancer development. Our systematic investigations, includes transcriptomic profiling, protein network, pharmacophore modeling, docking, binding free energy calculation, dynamics simulation, and quantum mechanics. The gene expression analysis on endometriosis and endometrial cancer was performed and showed 108 shared upregulated genes in both conditions. Further construction of interaction network with 108 genes showed intercellular adhesion molecule 1 (ICAM1) to be a crucial molecule with a high degree of connectivity that influences vital mechanisms related to cancer pathways. We then generated ligand-based pharmacophore models using established ICAM1 inhibitors. Among the models, the ADRRR_8 pharmacophore exhibited a robust area under curve (AUC = 0.83), was employed to screen 1739 anti-cancer drugs. On screening, 421 anti-cancer drugs displayed ICAM1-inhibiting pharmacophore features. Further, the docking of 421 drugs with ICAM1 showed lanreotide (-7.80 kcal/mol) with better affinity than the reference ICAM1 inhibitor (-3.59 kcal/mol). Further validation though binding free energy and dynamics simulation of the lanreotide-ICAM1 complex showed a high binding affinity of -55.90 kcal/mol and contributed stable confirmation. According to quantum chemical calculations, lanreotide's electronic properties favour ICAM1 binding with highest occupied molecular orbital was -6.91 eV and lowest unoccupied molecular orbital was -3.93 eV. Our study supports using lanreotide to treat endometriosis, which could delay or prevent endometrial cancer. These predictions need to be confirmed and examined to determine the use of lanreotide in endometriosis treatment.

In silico discovery of potential PPI inhibitors for anti-lung cancer activity by targeting the CCND1-CDK4 complex via the P21 inhibition mechanism.

Non-Small Cell Lung Cancer (NSCLC) is a prevalent and deadly form of lung cancer worldwide with a low 5-year survival rate. Current treatments have limitations, particularly for advanced-stage patients. P21, a protein that inhibits the CCND1-CDK4 complex, plays a crucial role in cell proliferation. Computer-Aided Drug Design (CADD) based on pharmacophores can screen and design PPI inhibitors targeting the CCND1-CDK4 complex. By analyzing known inhibitors, key pharmacophores are identified, and computational methods are used to screen potential PPI inhibitors. Molecular docking, pharmacophore matching, and structure-activity relationship studies optimize the inhibitors. This approach accelerates the discovery of CCND1-CDK4 PPI inhibitors for NSCLC treatment. Molecular dynamics simulations of CCND1-CDK4-P21 and CCND1-CDK4 complexes showed stable behavior, comprehensive sampling, and P21's impact on complex stability and hydrogen bond formation. A pharmacophore model facilitated virtual screening, identifying compounds with favorable binding affinities. Further simulations confirmed the stability and interactions of selected compounds, including 513457. This study demonstrates the potential of CADD in optimizing PPI inhibitors targeting the CCND1-CDK4 complex for NSCLC treatment. Extended simulations and experimental validations are necessary to assess their efficacy and safety.

Discovery of Novel Allosteric SHP2 Inhibitor Using Pharmacophore-Based Virtual Screening, Molecular Docking, Molecular Dynamics Simulation, and Principal Component Analysis.

SHP2 belongs to a cytoplasmic non-receptor protein tyrosine phosphatase class. It plays a critical role in the development of various cancers, such as gastric cancer, leukemia, and breast cancer. Thus, SHP2 has gained the interest of researchers as a potential target for inhibiting tumor cell proliferation in SHP2-dependent cancers. This study employed pharmacophore-based virtual screening, molecular docking, molecular dynamic (MD) simulations, MM/PBSA, and principal component analysis (PCA), followed by ADME prediction. We selected three potential hits from a collective database of more than one million chemical compounds. The stability of these selected hit-protein complexes was analyzed using 500 ns MD simulations and binding free energy calculations. The identified hits Lig_1, Lig_6, and Lig_14 demonstrated binding free energies of -161.49 kJ/mol, -151.28 kJ/mol, and -107.13 kJ/mol, respectively, compared to the reference molecule (SHP099) with a ΔG of -71.48 kJ/mol. Our results showed that the identified compounds could be used as promising candidates for selective SHP2 allosteric inhibition in cancer.

Network Pharmacology-Based Virtual Screening of Chemical Constituents from Vitexnegundo Linn's Discovered Novel Molecular Targets for Breast Cancer Treatment.

BACKGROUND: The Chinese chaste tree Vitexnegundo (VN) is a popular herb in South and Southeast Asia that has several health benefits, including the ability to inhibit tumor growth and induce apoptosis in multiple tumors. Literature revealed scanty research on breast cancer, with little focus on the molecular mechanism of the disease and an emphasis on targets, biological networks, and active components. Exploring natural compounds as possible therapeutic options is an old but still promising approach for drug discovery and development. This study used a thorough computational and statistical method to screen potential drug candidates. METHODS: The active ingredients and targets of VN were identified using SwissADME, SwissTargetPrediction, STITCH, IMPPAT database, KNapSAcK database, and literature. The OMIM and GeneCards databases were searched for possible targets related to breast cancer. The PASS online server was used to check the probability of active metabolite (Pa) against breast cancer. To build protein-protein interactions (PPI) networking, the intersection of disease and drug targets was uploaded to the STITCH database. Cytoscape software was used to analyze the topology parameters of networking to identify hub targets. Gene Ontology (GO) was analyzed using Metascape and ShinyGO, Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis was performed using the David database and SR plot, and the site of expression and protein domain were studied using FunRich. We employed AutoDockvina, Discovery Studio, and UCSF ChimeraX software and auxiliary tools for molecular docking and analysis. Zincpharmer was used for pharmacophore mapping. ADMET analysis was conducted using ADMETsar, Swiss ADME, ADMETLab servers, and mypresto using GROMACS for molecular dynamics simulation (MDS). RESULTS: A total of 65 targets and 21 active ingredients were identified. Further investigation was conducted on 20 hub targets selected through PPI networking construction. The enrichment analysis results indicated that the key factors were P, amyloid-beta response, cellular response to amyloid- beta, Pos. reg. of G2/M transition of the mitotic cell cycle, and response to a toxic substance. The molecular docking, pharmacophore mapping, and MD simulation results indicated that apigenin, kaempferol, and luteolin positively interacted with CDK1 and CDK6 proteins. CONCLUSION: This study is the first to use network pharmacology, molecular docking, pharmacophore mapping, and MD simulation to identify the active ingredients, molecular targets, and critical biological pathways responsible for VN anti-breast cancer. The study provides a theoretical basis for further research in this area.

Epigallocatechin gallate and curcumin inhibit Bcl-2: a pharmacophore and docking based approach against cancer.

The protein Bcl-2, well-known for its anti-apoptotic properties, has been implicated in cancer pathogenesis. Identifying the primary gene responsible for promoting improved cell survival and development has provided compelling evidence for preventing cellular death in the progression of malignancies. Numerous research studies have provided evidence that the abundance of Bcl-2 is higher in malignant cells, suggesting that suppressing Bcl-2 expression could be a viable therapeutic approach for cancer treatment. In this study, we acquired a compound collection using a database that includes constituents from Traditional Chinese Medicine (TCM). Initially, we established a pharmacophore model and utilized it to search the TCM database for potential compounds. Compounds with a fitness score exceeding 0.75 were selected for further analysis. The Absorption, Distribution, Metabolism, Excretion, and Toxicity (ADMET) analysis identified six compounds with favorable therapeutic characteristics. The compounds that successfully passed the initial screening process based on the pharmacodynamic model were subjected to further evaluation. Extra-precision (XP) docking was employed to identify the compounds with the most favorable XP docking scores. Further analysis using the Molecular Mechanics Generalized Born Surface Area (MM-GBSA) method to calculate the overall free binding energy. The binding energy between the prospective ligand molecule and the target protein Bcl-2 was assessed by a 100 ns molecular dynamics simulation for curcumin and Epigallocatechin gallate (EGCG). The findings of this investigation demonstrate the identification of a molecular structure that effectively inhibits the functionality of the Bcl-2 when bound to the ligand EGCG. Consequently, this finding presents a novel avenue for the development of pharmaceuticals capable of effectively addressing both inflammatory and tumorous conditions.

Navigating pharmacophore space to identify activity discontinuities: A case study with BCR-ABL.

The exploration of chemical space is a fundamental aspect of chemoinformatics, particularly when one explores a large compound data set to relate chemical structures with molecular properties. In this study, we extend our previous work on chemical space visualization at the pharmacophoric level. Instead of using conventional binary classification of affinity (active vs inactive), we introduce a refined approach that categorizes compounds into four distinct classes based on their activity levels: super active, very active, active, and inactive. This classification enriches the color scheme applied to pharmacophore space, where the color representation of a pharmacophore hypothesis is driven by the associated compounds. Using the BCR-ABL tyrosine kinase as a case study, we identified intriguing regions corresponding to pharmacophore activity discontinuities, providing valuable insights for structure-activity relationships analysis.

Identification of aryl hydrocarbon receptor allosteric antagonists from clinically approved drugs.

The human aryl hydrocarbon receptor (AhR), a ligand-dependent transcription factor, plays a pivotal role in a diverse array of pathways in biological and pathophysiological events. This position AhR as a promising target for both carcinogenesis and antitumor strategies. In this study we utilized computational modeling to screen and identify FDA-approved drugs binding to the allosteric site between α2 of bHLH and PAS-A domains of AhR, with the aim of inhibiting its canonical pathway activity. Our findings indicated that nilotinib effectively fits into the allosteric pocket and forms interactions with crucial residues F82, Y76, and Y137. Binding free energy value of nilotinib is the lowest among top hits and maintains stable within its pocket throughout entire (MD) simulations time. Nilotinib has also substantial interactions with F295 and Q383 when it binds to orthosteric site and activate AhR. Surprisingly, it does not influence AhR nuclear translocation in the presence of AhR agonists; instead, it hinders the formation of the functional AhR-ARNT-DNA heterodimer assembly, preventing the upregulation of regulated enzymes like CYP1A1. Importantly, nilotinib exhibits a dual impact on AhR, modulating AhR activity via the PAS-B domain and working as a noncompetitive allosteric antagonist capable of blocking the canonical AhR signaling pathway in the presence of potent AhR agonists. These findings open a new avenue for the repositioning of nilotinib beyond its current application in diverse diseases mediated via AhR.

Tail-approach based design, synthesis, and molecular modeling of benzenesulfonamides carrying thiadiazole and urea moieties as novel carbonic anhydrase inhibitors.

We synthesized herein 16 compounds (SUT1-SUT16) as potential carbonic anhydrase (CA) inhibitors utilizing the tail-approach design. Based on this strategy, we connected benzenesulfonamide, the zinc-binding scaffold, to different urea moieties with the 1,3,4-thiadiazole ring as a linker. We obtained the target compounds by the reaction of 4-(5-amino-1,3,4-thiadiazol-2-yl)benzenesulfonamide with aryl isocyanates. Upon confirmation of their structures, the compounds were screened for their ability to inhibit the tumor-related human (h) isoforms human carbonic anhydrase (hCA) IX and XII, as well as the physiologically dominant hCA I and II. Most of the molecules demonstrated Ki values ≤ 10 nM with different selectivity profiles. The binding modes of SUT9, SUT10, and SUT5, the most effective inhibitors of hCA II, IX, and XII, respectively, were predicted by molecular docking. SUT16 (4-{5-[3-(naphthalen-1-yl)ureido]-1,3,4-thiadiazol-2-yl}benzenesulfonamide) was found to be the most selective inhibitor of the cancer-associated isoforms hCA IX and XII over the off-target isoforms, hCAI and II. The interaction dynamics and stability of SUT16 within hCA IX and XII were investigated by molecular dynamics simulations as well as dynophore analysis. Based on computational data, increased hydrophobic contacts and hydrogen bonds in the tail part of these molecules within hCA IX and XII were found as favorable interactions leading to effective inhibitors of cancer-related isoforms.

Targeting cyclin-dependent kinase 2 CDK2: Insights from molecular docking and dynamics simulation - A systematic computational approach to discover novel cancer therapeutics.

Global public health is confronted with significant challenges due to the prevalence of cancer and the emergence of treatment resistance. This work focuses on the identification of cyclin-dependent kinase 2 (CDK2) through a systematic computational approach to discover novel cancer therapeutics. A ligand-based pharmacophore model was initially developed using a training set of seven potent CDK2 inhibitors. The obtained most robust model was characterized by three features: one donor (|Don|) and two acceptors (|Acc|). Screening this model against the ZINC database resulted in identifying 108 hits, which underwent further molecular docking studies. The docking results indicated binding affinity, with energy values ranging from -6.59 kcal mol⁻¹ to -7.40 kcal mol⁻¹ compared to the standard Roscovitine. The top 10 compounds (Z1-Z10) selected from the docking data were further screened for ADMET profiling, ensuring their compliance with pharmacokinetic and toxicological criteria. The top 3 compounds (Z1-Z3) chosen from the docking were subjected to Density Functional Theory (DFT) studies. They revealed significant variations in electronic properties, providing insights into the reactivity, stability, and polarity of these compounds. Molecular dynamics simulations confirmed the stability of the ligand-protein complexes, with acceptable RMSD and RMSF values. Specifically, compound Z1 demonstrated stability, around 2.4 Å, and maintained throughout the 100 ns simulation period with minimal conformational changes, stable RMSD, and consistent protein-ligand interactions.

Computational screening combined with well-tempered metadynamics simulations identifies potential TMPRSS2 inhibitors.

Type-II transmembrane serine proteases are effective pharmacological targets for host defence against viral entry and in certain cancer cell progressions. These serine proteases cleave viral spike proteins to expose the fusion peptide for cell entry, which is essential to the life cycle of the virus. TMPRSS2 inhibitors can also fight against respiratory viruses that employ them for cell entry. Our study combining virtual screening, all-atom molecular dynamics, and well-tempered metadynamics simulation identifies vicenin-2, neohesperidin, naringin, and rhoifolin as promising TMPRSS2 antagonists. The binding energies obtained are - 16.3, - 15.4, - 13.6, and - 13.8 kcal/mol for vicenin-2, neohesperidin, naringin, and rhoifolin respectively. The RMSD, RMSF, PCA, DCCM, and binding free energy profiles also correlate with the stable binding of these ligands at the active site of TMPRSS2. The study reveals that these molecules could be promising lead molecules for combating future outbreaks of coronavirus and other respiratory viruses.

TRAF6 Inhibitors from Marine Compound Library: Pharmacophore, Virtual Screening, Fragment Replacement, ADMET, and Molecular Dynamics.

TRAF6 is an E3 ubiquitin ligase that plays a crucial role in cell signaling. It is known that MMP is involved in tumor metastasis, and TRAF6 induces MMP-9 expression by binding to BSG. However, inhibiting TRAF6's ubiquitinase activity without disrupting the RING domain is a challenge that requires further research. To address this, we conducted computer-based drug screening to identify potential TRAF6 inhibitors. Using a ligand-receptor complex pharmacophore based on the inhibitor EGCG, known for its anti-tumor properties, we screened 52,765 marine compounds. After the molecular docking of 405 molecules with TRAF6, six compounds were selected for further analysis. By replacing fragments of non-binding compounds and conducting second docking, we identified two promising molecules, CMNPD9212-16 and CMNPD12791-8, with strong binding activity and favorable pharmacological properties. ADME and toxicity predictions confirmed their potential as TRAF6 inhibitors. Molecular dynamics simulations showed that CMNPD12791-8 maintained a stable structure with the target protein, comparable to EGCG. Therefore, CMNPD12791-8 holds promise as a potential inhibitor of TRAF6 for inhibiting tumor growth and metastasis.

Synthesis of a New Class of ß-Carbonyl Selenides Functionalized with Ester Groups with Antioxidant and Anticancer Properties-Part II.

A series of phenyl ß-carbonyl selenides with o-ester functionality substituted on the oxygen atom with chiral and achiral alkyl groups was synthesized. All compounds are the first examples of this type of organoselenium derivatives with an ester substituent in the ortho position. The obtained derivatives were tested as antioxidants and anticancer agents to see the influence of an ester functionality on the bioactivity of ß-carbonyl selenides by replacing the o-amide group with an o-ester group. The best results as an antioxidant agent were observed for O-((1R,2S,5R)-(-)-2-isopropyl-5-methylcyclohexyl)-2-((2-oxopropyl)selanyl)benzoate. The most cytotoxic derivative against breast cancer MCF-7 cell lines was O-(methyl)-2-((2-oxopropyl)selanyl)benzoate and against human promyelocytic leukemia HL-60 was O-(2-pentyl)-2-((2-oxopropyl)selanyl)benzoate.

Dual-targeted NAMPT inhibitors as a progressive strategy for cancer therapy.

In mammals, nicotinamide phosphoribosyltransferase (NAMPT) is a crucial enzyme in the nicotinamide adenine dinucleotide (NAD+) synthesis pathway catalyzing the condensation of nicotinamide (NAM) with 5-phosphoribosyl-1-pyrophosphate (PRPP) to produce nicotinamide mononucleotide (NMN). Given the pivotal role of NAD+ in a range of cellular functions, including DNA synthesis, redox reactions, cytokine generation, metabolism, and aging, NAMPT has become a promising target for many diseases, notably cancer. Therefore, various NAMPT inhibitors have been reported and classified as first and second-generation based on their chemical structures and design strategies, dual-targeted being one. However, most NAMPT inhibitors suffer from several limitations, such as dose-dependent toxicity and poor pharmacokinetic properties. Consequently, there is no clinically approved NAMPT inhibitor. Hence, research on discovering more effective and less toxic dual-targeted NAMPT inhibitors with desirable pharmacokinetic properties has drawn attention recently. This review summarizes the previously reported dual-targeted NAMPT inhibitors, focusing on their design strategies and advantages over the single-targeted therapies.

A drug repurposing study identifies novel FOXM1 inhibitors with in vitro activity against breast cancer cells.

FOXM1, a proto-oncogenic transcription factor, plays a critical role in cancer development and treatment resistance in cancers, particularly in breast cancer. Thus, this study aimed to identify potential FOXM1 inhibitors through computational screening of drug databases, followed by in vitro validation of their inhibitory activity against breast cancer cells. In silico studies involved pharmacophore modeling using the FOXM1 inhibitor, FDI-6, followed by virtual screening of DrugBank and Selleckchem databases. The selected drugs were prepared for molecular docking, and the crystal structure of FOXM1 was pre-processed for docking simulations. In vitro studies included MTT assays to assess cytotoxicity, and Western blot analysis to evaluate protein expression levels. Our study identified Pantoprazole and Rabeprazole as potential FOXM1 inhibitors through in silico screening and molecular docking. Molecular dynamics simulations confirmed stable interactions of these drugs with FOXM1. In vitro experiments showed both Pantoprazole and Rabeprazole exhibited strong FOXM1 inhibition at effective concentrations and that showed inhibition of cell proliferation. Rabeprazole showed the inhibitor activity at 10 µM in BT-20 and MCF-7 cell lines. Pantoprazole exhibited FOXM1 inhibition at 30 µM and in BT-20 cells and at 70 µM in MCF-7 cells, respectively. Our current study provides the first evidence that Rabeprazole and Pantoprazole can bind to FOXM1 and inhibit its activity and downstream signaling, including eEF2K and pEF2, in breast cancer cells. These findings indicate that rabeprazole and pantoprazole inhibit FOXM1 and breast cancer cell proliferation, and they can be used for FOXM1-targeted therapy in breast or other cancers driven by FOXM1.

Discovery of a novel DYRK1A inhibitor with neuroprotective activity by virtual screening and in vitro biological evaluation.

Dual-specificity tyrosine phosphorylation-regulated kinase 1A (DYRK1A) is implicated in accumulation of amyloid ß-protein (Aß) and phosphorylation of Tau proteins, and thus represents an important therapeutic target for neurodegenerative diseases. Though many DYRK1A inhibitors have been discovered, there is still no marketed drug targeting DYRK1A. This is partly due to the lack of effective and safe chemotypes. Therefore, it is still necessary to identify new classes of DYRK1A inhibitors. By performing virtual screening with the workflow mainly composed of pharmacophore modeling and molecular docking as well as the following DYRK1A inhibition assay, we identified compound L9, ((Z)-1-(((5-phenyl-1H-pyrazol-4-yl)methylene)-amino)-1H-tetrazol-5-amine), as a moderately active DYRK1A inhibitor (IC50: 1.67 µM). This compound was structurally different from the known DYRK1A inhibitors, showed a unique binding mode to DYRK1A. Furthermore, compound L9 showed neuroprotective activity against okadaic acid (OA)-induced injury in the human neuroblastoma cell line SH-SY5Y by regulating the expression of Aß and phosphorylation of Tau protein. This compound was neither toxic to the SH-SY5Y cells nor to the human normal liver cell line HL-7702 (IC50: >100 µM). In conclusion, we have identified a novel DYRK1A inhibitor with neuroprotective activity through virtual screening and in vitro biological evaluation, which holds the promise for further study.

In silico Exploration of a Novel ICMT Inhibitor with More Solubility than Cysmethynil against Membrane Localization of KRAS Mutant in Colorectal Cancer.

BACKGROUND: ICMT (isoprenylcysteine carboxyl methyltransferase) is an enzyme that plays a key role in the post-translational modification of the K-Ras protein. The carboxyl methylation of this protein by ICMT is important for its proper localization and function. Cysmethynil (2-[5-(3-methylphenyl)-l-octyl-lH-indolo-3-yl] acetamide) causes K-Ras mislocalization and interrupts pathways that control cancer cell growth and division through inhibition of ICMT, but its poor water solubility makes it difficult and impractical for clinical use. This indicates that relatively high amounts of cysmethynil would be required to achieve an effective dose, which could result in significant adverse effects in patients. OBJECTIVE: The general objective of this work was to find virtually new compounds that present high solubility in water and are similar to the pharmacological activity of cysmethynil. METHODS: Pharmacophore modeling, pharmacophore-based virtual screening, prediction of ADMET properties (absorption, distribution, metabolism, excretion, and toxicity), and water solubility were performed to recover a water-soluble molecule that shares the same chemical characteristics as cysmethynil using Discovery Studio v16.1.0 (DS16.1), SwissADME server, and pkCSM. RESULTS: In this study, ten pharmacophore model hypotheses were generated by exploiting the characteristics of cysmethynil. The pharmacophore model validated by the set test method was used to screen the "Elite Library®" and "Synergy Library" databases of Asinex. Only 1533 compounds corresponding to all the characteristics of the pharmacophore were retained. Then, the aqueous solubility in water at 25°C of these 1533 compounds was predicted by the Cheng and Merz model. Among these 1533 compounds, two had the optimal water solubility. Finally, the ADMET properties and Log S water solubility by three models (ESOL, Ali, and SILICOS-IT) of the two compounds and cysmethynil were compared, resulting in compound 2 as a potential inhibitor of ICMT. CONCLUSION: According to the results obtained, the identified compound presented a high solubility in water and could be similar to the pharmacological activity of cysmethynil.

Structural and molecular insights from dual inhibitors of EGFR and VEGFR2 as a strategy to improve the efficacy of cancer therapy.

Epidermal growth factor receptor (EGFR) and vascular endothelial growth factor 2 (VEGFR2) are known as valid targets for cancer therapy. Overexpression of EGFR induces uncontrolled cell proliferation and VEGF expression triggering angiogenesis via VEGFR2 signaling. On the other hand, VEGF expression independent of EGFR signaling is already known as one of the mechanisms of resistance to anti-EGFR therapy. Therefore, drugs that act as dual inhibitors of EGFR and VEGFR2 can be a solution to the problem of drug resistance and increase the effectiveness of therapy. In this review, we summarize the relationship between EGFR and VEGFR2 signal transduction in promoting cancer growth and how their kinase domain structures can affect the selectivity of an inhibitor as the basis for designing dual inhibitors. In addition, several recent studies on the development of dual EGFR and VEGFR2 inhibitors involving docking simulations were highlighted in this paper to provide some references such as pharmacophore features of inhibitors and key residues for further research, especially in computer-aided drug design.