Identification of 1H-purine-2,6-dione derivative as a potential SARS-CoV-2 main protease inhibitor: molecular docking, dynamic simulations, and energy calculations

From pixels to druggable leads: A CADD strategy for the design and synthesis of potent DDR1 inhibitors

BACKGROUND AND OBJECTIVE

While numerous in silico tools exist for target-based drug discovery, the inconsistent integration of in vitro data with predictive models hinders research and development productivity. This is particularly apparent during the Hit-to-Lead stage, where unreliable in-silico tools often lead to suboptimal lead selection. Herein, we address this challenge by presenting a CADD-guided pipeline that successfully integrates rational drug design with in-silico hits to identify a promising DDR1 lead.

METHODS

2 × 1000 ns MD simulations along with their respective FEL and MMPBSA analyses were employed to guide the rational design and synthesis of 12 novel compounds which were evaluated for their DDR inhibition.

RESULTS

The molecular dynamics investigation of the initial hit led to the identification of key structural features within the DDR1 binding pocket. The identified key features were used to guide the rational design and synthesis of twelve novel derivatives. SAR analysis, biological evaluation, molecular dynamics, and free energy calculations were carried out for the synthesized derivatives to understand their mechanism of action. Compound 4c exhibited the strongest inhibition and selectivity for DDR1, with an IC50 of 0.11 µM.

CONCLUSIONS

The MD simulations led to the identification of a key hydrophobic groove in the DDR1 binding pocket. The integrated approach of SAR analysis with molecular dynamics led to the identification of compound 4c as a promising lead for further development of potent and selective DDR1 inhibitors. Moreover, this work establishes a protocol for translating in silico hits to real world bioactive druggable leads.

A novel indole derivative, 2-{3-[1-(benzylsulfonyl)piperidin-4-yl]-2-methyl-1H-indol-1-yl}-1-(pyrrolidin-1-yl)ethenone, suppresses hedgehog signaling and drug-resistant tumor growth

The Hedgehog (Hh) signaling pathway plays important roles in various physiological functions. Several malignancies, such as basal cell carcinoma (BCC) and medulloblastoma (MB), have been linked to the aberrant activation of Hh signaling. Although therapeutic drugs have been developed to inhibit Hh pathway-dependent cancer growth, drug resistance remains a major obstacle in cancer treatment. Here, we show that the newly identified, 2-{3-[1-(benzylsulfonyl)-1,2,3,6-tetrahydropyridin-4-yl]-2-methyl-1H-indol-1-yl}-1-(pyrrolidin-1-yl)ethenone analog (LKD1214) exhibits comparable potency to vismodegib in suppressing the Hh pathway activation. LKD1214 represses Smoothened (SMO) activity by blocking its ciliary translocation. Interestingly, we also identified that it has a distinctive binding interface with SMO compared with other SMO-regulating chemicals. Notably, it maintains an inhibitory activity against the SmoD477H mutant, as observed in a patient with vismodegib-resistant BCC. Furthermore, LKD1214 inhibits tumor growth in the mouse model of MB. Collectively, these findings suggest that LKD1214 has the therapeutic potential to overcome drug-resistance in Hh-dependent cancers.

Antiviral Potential of Fucoxanthin, an Edible Carotenoid Purified from Sargassum siliquastrum, against Zika Virus

Considering the lack of antiviral drugs worldwide, we investigated the antiviral potential of fucoxanthin, an edible carotenoid purified from Sargassum siliquastrum, against zika virus (ZIKV) infection. The antiviral activity of fucoxanthin was assessed in ZIKV-infected Vero E6 cells, and the relevant structural characteristics were confirmed using molecular docking and molecular dynamics (MD) simulation. Fucoxanthin decreased the infectious viral particles and nonstructural protein (NS)1 mRNA expression levels at concentrations of 12.5, 25, and 50 µM in ZIKV-infected cells. Fucoxanthin also decreased the increased mRNA levels of interferon-induced proteins with tetratricopeptide repeat 1 and 2 in ZIKV-infected cells. Molecular docking simulations revealed that fucoxanthin binds to three main ZIKV proteins, including the envelope protein, NS3, and RNA-dependent RNA polymerase (RdRp), with binding energies of -151.449, -303.478, and -290.919 kcal/mol, respectively. The complex of fucoxanthin with RdRp was more stable than RdRp protein alone based on MD simulation. Further, fucoxanthin bonded to the three proteins via repeated formation and disappearance of hydrogen bonds. Overall, fucoxanthin exerts antiviral potential against ZIKV by affecting its three main proteins in a concentration-dependent manner. Thus, fucoxanthin isolated from S. siliquastrum is a potential candidate for treating zika virus infections.

Unveiling the ESR1 Conformational Stability and Screening Potent Inhibitors for Breast Cancer Treatment

BACKGROUND

The current study recognizes the significance of estrogen receptor alpha (ERα) as a member of the nuclear receptor protein family, which holds a central role in the pathophysiology of breast cancer. ERα serves as a valuable prognostic marker, with its established relevance in predicting disease outcomes and treatment responses.

METHODS

In this study, computational methods are utilized to search for suitable drug-like compounds that demonstrate analogous ligand binding kinetics to ERα.

RESULTS

Docking-based simulation screened out the top 5 compounds - ZINC13377936, NCI35753, ZINC35465238, ZINC14726791, and NCI663569 against the targeted protein. Further, their dynamics studies reveal that the compounds ZINC13377936 and NCI35753 exhibit the highest binding stability and affinity.

CONCLUSION

Anticipating the competitive inhibition of ERα protein expression in breast cancer, we envision that both ZINC13377936 and NCI35753 compounds hold substantial promise as potential therapeutic agents. These candidates warrant thorough consideration for rigorous In vitro and In vivo evaluations within the context of clinical trials. The findings from this current investigation carry significant implications for the advancement of future diagnostic and therapeutic approaches for breast cancer.

Machine Learning-Based Approach to Developing Potent EGFR Inhibitors for Breast Cancer-Design, Synthesis, and In Vitro Evaluation

The epidermal growth factor receptor (EGFR) is vital for regulating cellular functions, including cell division, migration, survival, apoptosis, angiogenesis, and cancer. EGFR overexpression is an ideal target for anticancer drug development as it is absent from normal tissues, marking it as tumor-specific. Unfortunately, the development of medication resistance limits the therapeutic efficacy of the currently approved EGFR inhibitors, indicating the need for further development. Herein, a machine learning-based application that predicts the bioactivity of novel EGFR inhibitors is presented. Clustering of the EGFR small-molecule inhibitor (∼9000 compounds) library showed that N-substituted quinazolin-4-amine-based compounds made up the largest cluster of EGFR inhibitors (∼2500 compounds). Taking advantage of this finding, rational drug design was used to design a novel series of 4-anilinoquinazoline-based EGFR inhibitors, which were first tested by the developed artificial intelligence application, and only the compounds which were predicted to be active were then chosen to be synthesized. This led to the synthesis of 18 novel compounds, which were subsequently evaluated for cytotoxicity and EGFR inhibitory activity. Among the tested compounds, compound 9 demonstrated the most potent antiproliferative activity, with 2.50 and 1.96 μM activity over MCF-7 and MDA-MB-231 cancer cell lines, respectively. Moreover, compound 9 displayed an EGFR inhibitory activity of 2.53 nM and promising apoptotic results, marking it a potential candidate for breast cancer therapy.

Integration of Hybridization Strategies in Pyridine-Urea Scaffolds for Novel Anticancer Agents: Design, Synthesis, and Mechanistic Insights

Annually, millions of new cancer cases are reported, leading to millions of deaths worldwide. Among the newly reported cases, breast and colon cancers prevail as the most frequently detected variations. To effectively counteract this rapid increase, the development of innovative therapies is crucial. Small molecules possessing pyridine and urea moieties have been reported in many of the currently available anticancer agents, especially VEGFR2 inhibitors. With this in mind, a rational design approach was employed to create hybrid small molecules combining urea and pyridine. These synthesized compounds underwent in vitro testing against breast and colon cancer cell lines, revealing potent submicromolar anticancer activity. Compound 8a, specifically, exhibited an impressive GI₅₀ value of 0.06 μM against the MCF7 cancer cell line, while compound 8h displayed the highest cytotoxic activity against the HCT116 cell line, with a GI₅₀ of 0.33 ± 0.042 μM. Notably, compounds 8a, 8h, and 8i demonstrated excellent safety profiles when tested on normal cells. Molecular docking, dynamic studies, and free energy calculations were employed to validate the affinity of these compounds as VEGFR2 inhibitors.

Identification of Potent hDHODH Inhibitors for Lung Cancer via Virtual Screening of a Rationally Designed Small Combinatorial Library

Cancer is characterized by altered cellular metabolism, and metabolic enzymes are considered as a promising target for anticancer therapy. Pyrimidine metabolism dysregulation is associated with various types of cancer, particularly lung cancer, which is one of the leading causes of cancer-related mortality worldwide. Recent studies have shown that small-cell lung cancer cells are particularly reliant on the pyrimidine biosynthesis pathway and are sensitive to its disruption. DHODH, the rate-limiting enzyme of the de novo pyrimidine production pathway, is essential in the production of RNA and DNA and is overexpressed in malignancies such as AML, skin cancer, breast cancer, and lung cancer, thereby highlighting DHODH as a viable target for developing drugs to combat lung cancer. Herein, rational drug design and computational techniques were used to discover novel DHODH inhibitors. A small combinatorial library was generated, and the top hits were synthesized and tested for anticancer activity against three lung cancer cell lines. Among the tested compounds, compound 5c possessed a stronger cytotoxicity (TC₅₀ of 11 μM) compared to the standard FDA-approved drug (Regorafenib, TC₅₀ of 13 μM) on the A549 cell line. Furthermore, compound 5c demonstrated potent inhibitory activity against hDHODH at a nanomolar level of 421 nM. DFT, molecular docking, molecular dynamic simulations, and free energy calculations were also carried out to understand the inhibitory mechanisms of the synthesized scaffolds. These in silico studies identified key mechanisms and structural features that will be crucial for future studies.

Discovery and optimization of natural-based nanomolar c-Kit inhibitors via in silico and in vitro studies

c-Kit is a receptor tyrosine kinase which is involved in intracellular signaling and mutations of c-Kit have been associated with various types of cancers. Investigations have shown that inhibition of c-Kit, using tyrosine kinase inhibitors, yielded promising results in cancer treatment marking it as a promising target for cancer therapy. However, the emerging resistance for the current therapy necessitates the development of more potent inhibitors which are not affected by these mutations. Herein, virtual screening of a library of natural-based compounds yielded three hits (2, 5 and 6) which possessed nanomolar inhibitory (2.02, 4.33 and 2.80 nM, respectively) activity when tested in vitro against c-Kit. Single point mutation docking studies showed the hits to be unaffected by the most common resistance mutation in imatinib-resistant cells, mutation of Val654. Although, the top hits exhibited around 3000 higher inhibitory potency toward c-Kit when compared to imatinib (5.4 µM), previous studies have shown that they are metabolically unstable. Fragment-based drug design approaches were then employed to enhance binding affinity of the top hit and make it more metabolically stable. Screening of the generated fragments yielded a new derivative, F1, which demonstrated stronger binding affinity, stability and binding free energy when compared to the hit compound 2.Communicated by Ramaswamy H. Sarma.