Integrated computational approach identifies potential inhibitors of ASK1-(JNK/P38) interaction signaling: new insights into cancer therapeutics.

Cancers are characterized by the aberrant expression of certain genes that trigger a cascade of molecular events that culminate in dysregulated cell division. Consequently, the inhibition of the products of these expressedgenes has emerged as a rational approach in cancer therapy. The apoptosis signal-regulating kinase 1 (ASK1) protein, encoded by the mitogen-activated protein kinase kinase kinase 5 (MAP3K5) gene, plays pertinent roles in the mediation of cell death induced by stress and inflammation, andis often found at elevated levels in cancer. Consequently, it has emerged as a molecular target for the development of potential chemotherapeutics through identification of selective inhibitors. However, there is still dearth of ASK1 inhibitors in clinical use. Hence, molecular modelling approaches were employed in this study to discover potential ASK1 inhibitors from phytochemicals. Twenty-five phytocompounds from four medicinal plants were tested for their inhibitory prowess via molecular docking. Interestingly, all the compounds exhibited promising inhibitory potentials for ASK1. However, further subjection to filtering procedures via different pipelines including drug-likeness evaluation, pharmacokinetics screening, toxicity profiling, and better affinities compared to the approved inhibitor resulted in three hit compounds namely ellagic acid, luteolin, and kaempferol with suitable properties. Profiling of the interactions formed between the hit\compounds and the targets revealed several interactions that were not present in that of the approved inhibitor, while molecular dynamics (MD) simulation revealed the complexes formed as stable. Conclusively, this study identified three compounds with ASK1 inhibitory potentials that are worthy of further exploration in in vitro and in vivo studies.Communicated by Ramaswamy H. Sarma.

Integrating biocomputational techniques for Breast cancer drug discovery via the HER-2, BCRA, VEGF and ER protein targets.

Computational modelling remains an indispensable technique in drug discovery. With myriad of high computing resources, and improved modelling algorithms, there has been a high-speed in the drug development cycle with promising success rate compared to the traditional route. For example, lapatinib; a well-known anticancer drug with clinical applications was discovered with computational drug design techniques. Similarly, molecular modelling has been applied to various disease areas ranging from cancer to neurodegenerative diseases. The techniques ranges from high-throughput virtual screening, molecular mechanics with generalized Born and surface area solvation (MM/GBSA) to molecular dynamics simulation. This review focuses on the application of computational modelling tools in the identification of drug candidates for Breast cancer. First, we begin with a succinct overview of molecular modelling in the drug discovery process. Next, we take note of special efforts on the developments and applications of combining these techniques with particular emphasis on possible breast cancer therapeutic targets such as estrogen receptor (ER), human epidermal growth factor receptor 2 (HER2), vascular endothelial growth factor (VEGF), breast cancer gene 1 (BRCA1), and breast cancer gene 2 (BRCA2). Finally, we discussed the search for covalent inhibitors against these receptors using computational techniques, advances, pitfalls, possible solutions, and future perspectives.

Design of small molecules for CDK-2 inhibition in colorectal cancer based on substructure search.

The global frequency of colorectal cancer motivates extensive drug discovery efforts. CDK2, a key member of the CDK family, has been linked to tumor progression, unregulated cell proliferation, and growth promotion. Water-soluble flavonoids with a fast metabolism called anthocyanins have been shown to have a variety of pharmacological properties, including anti-cancer properties. This study aims to find possible CDK2 inhibitors from Anthocyanin-like molecules. Anthocyanins sourced from PubChem were screened using a virtual screening approach that included a KNIME workflow, QSAR-model, Pharmacophore hypothesis, and a structure-based screening to identify compounds with a better binding affinity and predicted bioactivity compared to the standard, Sorafenib. The top compounds were subjected to a 100 ns MD simulation to confirm their stability at the active site. Compounds 1-5 were shown to have higher binding affinity and bioactivity in this study. These substances interacted with the critical amino acids (LEU 83, ASP 145 and LYS 89) at CDK2's active site. Compared to the reference with a pIC50 value of 6.003 nM, the top compounds listed have superior predicted bioactivity ranging from 6.539 to 6.36 nM. Also, ADMET predictions predicted that Compounds 1-5 were not carcinogenic and not a p-glycoprotein substrate. MD simulation also validated Compound 1's stability at the active site compared to the standard. This study uncovers potential CDK2 inhibitors with good binding affinities, shedding light on their interactions with the target protein. While promising, further in vivo and in vitro investigations are essential to validate the anticancer potential of these compounds.Communicated by Ramaswamy H. Sarma.

Identification of bioactive compounds from Vaccinium vitis-idaea L. (Lingonberry) as inhibitors for treating KRAS-associated cancer: a computational approach.

Lung cancer is the cancer of the lung's epithelial cells typically characterized by difficulty breathing, chest pain, blood-stained coughs, headache, and weight loss. If left unmanaged, lung cancer can spread to other body parts. While several treatment methods exist for managing lung cancer, exploring natural plant sources for developing therapeutics offers great potential in complementing other treatment approaches. In this study, we evaluated the bioactive compounds in Vaccinium vitis-idaea for treating KRAS-associated lung cancer types. In this study, we concentrated on inhibiting the mutated Kirsten rat sarcoma viral oncogene homolog (KRAS) by targeting an associated protein (Phosphodiesterase 6δ) to which KRAS form complexes. We evaluated bioactive compounds from Lingonberry (Vaccinium vitis-idaea L.), adopting computational approaches such as molecular docking, molecular dynamics simulation, molecular mechanics/generalized Born surface area (MM/GBSA) calculations, and pharmacokinetics analysis. A total of 26 out of 39 bioactive compounds of Vaccinium vitis-idaea L. had a higher binding affinity to the target receptor than an approved drug, Sotorasib. Also, further analyses of all lead/top compounds in this study identified (+)-Catechin (Cianidanol), Arbutin, Resveratrol, and Sinapic acid, to be potential drug candidates that could be pursued. In sum, Arbutin, (+)-Catechin, and Sinapic acid are predicted to be the top compound of Vaccinium vitis-idaea L. because of their pharmacokinetic properties and drug-likeness attributes. Also, their stability to the target receptor makes them a potential drug candidate that could be explored for treating KRAS mutation-associated lung cancer. Supplementary Information: The online version contains supplementary material available at 10.1007/s40203-023-00165-1.

QSAR-based virtual screening of traditional Chinese medicine for the identification of mitotic kinesin Eg5 inhibitors.

Cell division is a crucial process for the growth and development of all living organisms. Unfortunately, uncontrolled cell division and growth is a hallmark of cancer, leading to the formation of tumors. The Human Eg5 protein, also known as the mitotic kinesin Eg5, plays a vital role in the regulation of cell division and its dysfunction has been linked to cancer development. This study aimed to identify new inhibitors of the Human Eg5 protein. Over 2000 Traditional Chinese Medicine (TCM) compounds were screened through a combination of virtual and structure-based screening methods. The top five compounds (Compounds 1-5) showed improved binding affinity to Human Eg5 compared to the standard drug Monastrol, as demonstrated by docking and MMGBSA scores, as well as interactions with key amino acids GLY 116 and GLY 118. The potential absorption and bioactivity of these compounds were also predicted through ADMET properties and a QSAR model, respectively, and showed improved results compared to the standard. Further quantum mechanics docking confirmed the better binding affinity of the lead compound, Compound 1. Our findings highlight Compound 1-5 as promising hits for inhibiting Human Eg5 and the need for experimental validation of their potential in treating cancer.

Discovery of putative inhibitors against main drivers of SARS-CoV-2 infection: Insight from quantum mechanical evaluation and molecular modeling.

SARS-CoV-2 triggered a worldwide medical crisis, affecting the world's social, emotional, physical, and economic equilibrium. However, treatment choices and targets for finding a solution to COVID-19's threat are becoming limited. A viable approach to combating the threat of COVID-19 is by unraveling newer pharmacological and therapeutic targets pertinent in the viral survival and adaptive mechanisms within the host biological milieu which in turn provides the opportunity to discover promising inhibitors against COVID-19. Therefore, using high-throughput virtual screening, manually curated compounds library from some medicinal plants were screened against four main drivers of SARS-CoV-2 (spike glycoprotein, PLpro, 3CLpro, and RdRp). In addition, molecular docking, Prime MM/GBSA (molecular mechanics/generalized Born surface area) analysis, molecular dynamics (MD) simulation, and drug-likeness screening were performed to identify potential phytodrugs candidates for COVID-19 treatment. In support of these approaches, we used a series of computational modeling approaches to develop therapeutic agents against COVID-19. Out of the screened compounds against the selected SARS-CoV-2 therapeutic targets, only compounds with no violations of Lipinski's rule of five and high binding affinity were considered as potential anti-COVID-19 drugs. However, lonchocarpol A, diplacol, and broussonol E (lead compounds) were recorded as the best compounds that satisfied this requirement, and they demonstrated their highest binding affinity against 3CLpro. Therefore, the 3CLpro target and the three lead compounds were selected for further analysis. Through protein-ligand mapping and interaction profiling, the three lead compounds formed essential interactions such as hydrogen bonds and hydrophobic interactions with amino acid residues at the binding pocket of 3CLpro. The key amino acid residues at the 3CLpro active site participating in the hydrophobic and polar inter/intra molecular interaction were TYR54, PRO52, CYS44, MET49, MET165, CYS145, HIS41, THR26, THR25, GLN189, and THR190. The compounds demonstrated stable protein-ligand complexes in the active site of the target (3CLpro) over a 100 ns simulation period with stable protein-ligand trajectories. Drug-likeness screening shows that the compounds are druggable molecules, and the toxicity descriptors established that the compounds demonstrated a good biosafety profile. Furthermore, the compounds were chemically reactive with promising molecular electron potential properties. Collectively, we propose that the discovered lead compounds may open the way for establishing phytodrugs to manage COVID-19 pandemics and new chemical libraries to prevent COVID-19 entry into the host based on the findings of this computational investigation.

Structure-based discovery of selective CYP17A1 inhibitors for Castration-resistant prostate cancer treatment.

Prostate cancer (PCa) is the most common malignancy found in men and the second leading cause of cancer-related death worldwide. Castration-resistant PCa (CRPC) is defined by PCa cells that stop responding to hormone therapy. Cytochrome P450 17α-hydroxylase/17,20-lyase (CYP17A1) plays a critical role in the biosynthesis of androgens in humans. Androgen signaling cascade is a principal survival pathway for PCa cells and androgen-deprivation therapy (ADT) remains the key treatment for patients marked with locally advanced and metastatic PCa cells. Available synthetic drugs have been reported for toxicity, drug resistance, and decreasing efficacy. Thus, the design of novel selective inhibitors of CYP17A1 lyase would help circumvent associated side effects and improve pharmacological activities. Therefore, we employed structural bioinformatics techniques via molecular docking; molecular mechanics generalized born surface area (MM-GBSA), molecular dynamics (MD) simulation, and pharmacokinetic study to identify putative CYP17A1 lyase inhibitors. The results of the computational investigation showed that the Prunus dulcis compounds exhibited higher binding energy than the clinically approved abiraterone acetate. The stability of the ligand with the highest binding affinity (quercetin-3-o-rutinoside) was observed during MD simulation for 10 ns. Quercetin-3-o-rutinoside was observed to be stable within the active site of CYP17A1Lyase throughout the simulation period. The result of the pharmacokinetic study revealed that these compounds are promising therapeutic agents. Collectively, this study proposed that bioactive compounds from P. dulcis may be potential selective inhibitors of CYP17A1Lyase in CRPC treatments.

Computational Evaluation of Bioactive Compounds from Colocasia affinis Schott as a Novel EGFR Inhibitor for Cancer Treatment.

INTRODUCTION: Epidermal growth factor receptor (EGFR) is a transmembrane protein that belongs to the ErbB/HER-family of tyrosine kinase receptors. Somatic mutations and overexpression of EGFR have been reported to play a vital role in cancer cell development and progression, including cell proliferation, differentiation, angiogenesis, apoptosis, and metastatic spread. Hence, EGFR is an important therapeutic target for the treatment of various types of epithelial cancers. Somatic mutations have led to resistance to clinically approved synthetic EGFR inhibitors. Furthermore, synthetic EGFR inhibitors have been associated with several side effects. Thus, there is a need to develop novel EGFR inhibitors with an acceptable biosafety profile and high efficacy. METHODS: Herein, we employed structural bioinformatics and theoretical chemistry techniques via molecular docking, molecular mechanics generalized Born surface area (MM-GBSA) calculation, density functional theory analysis (DFT), and pharmacokinetic study to identify novel EGFR inhibitors. RESULTS: The stringent molecular docking and MM-GBSA calculations identified MET 793, LYS 745, PHE 723, ASP 855, ARG 411, and THR 854 as principal amino acid residues for EGFR-ligands interactions. Furthermore, Colocasia affinis Schott compounds exhibited higher binding energy and more stable interactions than the reference compound (gefitinib). DFT analysis also ascertains better bioactivity and chemical reactivity of C. affinis Schott with favorable intramolecular charge transfer between electron-donor and electron acceptor groups. The pharmacokinetic profile of C. affinis Schott bioactive compounds satisfies Lipinski's rule of five assessment. CONCLUSION: Collectively, C. affinis Schott compounds demonstrated higher inhibitory potentials against EGFR and better pharmacological properties when compared with gefitinib. C. affinis Schott compounds are therefore suggested as promising therapeutic EGFR inhibitors for cancer treatment.

Anticancer Potential of Moringa oleifera on BRCA-1 Gene: Systems Biology.

Breast cancer has consistently been a global challenge that is prevalent among women. There is a continuous increase in the high number of women mortality rates because of breast cancer and affecting nations at all modernization levels. Women with high-risk factors, including hereditary, obesity, and menopause, have the possibility of developing breast cancer growth. With the advent of radiotherapy, chemotherapy, hormone therapy, and surgery in breast cancer treatment, breast cancer survivors have increased. Also, the design and development of drugs targeting therapeutic enzymes effectively treat the tumour cells early. However, long-term use of anticancer drugs has been linked to severe side effects. This research aims to develop potential drug candidates from Moringa oleifera, which could serve as anticancer agents. In silico analysis using Schrödinger Molecular Drug Discovery Suite and SWISS ADME was employed to determine the therapeutic potential of phytochemicals from M oleifera against breast cancer via molecular docking, pharmacokinetic parameters, and drug-like properties. The result shows that rutin, vicenin-2, and quercetin-3-O-glucoside have the highest binding energy of -7.522, -6.808, and -6.635 kcal/mol, respectively, in the active site of BRCA-1. The essential amino acids involved in the protein-ligand interaction following active site analysis are ASN 1678, ASN 1774, GLY 1656, LEU 1657, GLN 1779, LYS 1702, SER 1655, PHE 1662, ARG 1699, GLU 1698, and VAL 1654. Thus, we propose that bioactive compounds from M oleifera may be potential novel drug candidates in the treatment of breast cancer.