Development of a novel class of B-Raf(V600E)-selective inhibitors through virtual screening and hierarchical hit optimization

Computational Approaches: A New Frontier in Cancer Research

Cancer is a broad category of disease that can start in virtually any organ or tissue of the body when aberrant cells assault surrounding organs and proliferate uncontrollably. According to the most recent statistics, cancer will be the cause of 10 million deaths worldwide in 2020, accounting for one death out of every six worldwide. The typical approach used in anti-cancer research is highly time-consuming and expensive, and the outcomes are not particularly encouraging. Computational techniques have been employed in anti-cancer research to advance our understanding. Recent years have seen a significant and exceptional impact on anticancer research due to the rapid development of computational tools for novel drug discovery, drug design, genetic studies, genome characterization, cancer imaging and detection, radiotherapy, cancer metabolomics, and novel therapeutic approaches. In this paper, we examined the various subfields of contemporary computational techniques, including molecular docking, artificial intelligence, bioinformatics, virtual screening, and QSAR, and their applications in the study of cancer.

Supramolecular polymerization of thiobarbituric acid naphthalene dye

2-Thiobarbituric acid-functionalized naphthalene dye selectively self-assembles into crystalline fibers to show material properties that are different from those of a previously reported oxo-barbituric acid derivative affording curved supramolecular polymers via...

Systemic review on B-RafV600E mutation as potential therapeutic target for the treatment of cancer

Cancer is one of the major public catastrophes worldwide and as per WHO, cancer is the leading cause of death universally after CVS disorders accounting for 9.6 million deaths in 2018. WHO statistics revealed five dangerous types of cancer viz. lung, breast, colorectal, prostate and skin. In male, lung cancer causes highest death, while in female, breast cancer causes the most. Alteration in MAPK signalling pathway plays a significant role in majority of cancer cases. Raf protein is activated by phosphorylation via downstream regulation of the MAPK pathway. Raf composed of 3 subtypes, viz. A-Raf, B-Raf, and C-Raf. B-Raf kinase plays a significant role in healthy cell growth in the MAPK pathway and the problem associated with B-Raf mutation leads to the development of cancer and other diseases. The progression of mutant B-Raf (B-Raf^V600E) protein is higher in cancer as compare to other diseases. In 2002, B-Raf^V600E mutation was identified for the first time in the development of cancer. The frequency of B-Raf^V600E mutation is higher in melanoma, thyroid, colorectal and ovarian cancer. We have covered small molecule B-Raf^V600E inhibitors reported in various literatures; from 2002 to 2020 and also covered clinical trial data. To widen the scope of readers, we compiled details of small molecules, specifically inhibiting B-Raf^V600E mutant and showing anti-proliferative activity against various cancer cell lines along with in-vivo data. We believe that the information covered here will be important in signifying the potentials of B-Raf^V600E mutation and its inhibitors as potent anticancer agents.

A review of ligand-based virtual screening web tools and screening algorithms in large molecular databases in the age of big data

Virtual screening has become a widely used technique for helping in drug discovery processes. The key to this success is its ability to aid in the identification of novel bioactive compounds by screening large molecular databases. Several web servers have emerged in the last few years supplying platforms to guide users in screening publicly accessible chemical databases in a reasonable time. In this review, we discuss a representative set of online virtual screening servers and their underlying similarity algorithms. Other related topics, such as molecular representation or freely accessible databases are also treated. The most relevant contributions to this review arise from critical discussions concerning the pros and cons of servers and algorithms, and the challenges that future works must solve in a virtual screening framework.

Design and synthesis of novel thiobarbituric acid derivatives targeting both wild-type and BRAF-mutated melanoma cells

A series of novel thio- and seleno-barbituric acid derivatives were synthesized by varying the substituents at N1 and N3 (ethyl, methyl, allyl, and phenyl), and C5 tethered with dienyl and trienyl moieties attached to substituents such as phenyl, 2-furanyl, 2-thiophenyl, 1-naphthyl, and 3-pyridyl. The cytotoxic potential of these derivatives was evaluated by using MTT assay against melanoma cell lines expressing either wild-type (CHL-1) or mutant (UACC 903) BRAF gene. Among all, 2b and 8b were identified as the most potent compounds. Both 2b and 8b inhibited viability of various melanoma cells and induced cell death as evidenced by Live and Dead assay. Western blot analysis showed that they induce PARP cleavage and inhibit anti-apoptotic Bcl-2, Bcl-xL and Survivin in a dose-dependent manner within 24 h of the treatment. Novel thiobarbituric acid analogs also inhibited viability of various other solid tumor cell lines, such as pancreatic, breast, and colon. Overall, 2b, 2d, and 8b emerged as the most effective compounds and make good leads for the development of future therapeutic agents.

Integrating docking scores and key interaction profiles to improve the accuracy of molecular docking: towards novel B-RafV600E inhibitors

A set of ninety-eight B-RafV600E inhibitors was used for the development of a molecular docking based QSAR model using linear and non-linear regression models. The integration of docking scores and key interaction profiles significantly improved the accuracy of the QSAR models, providing reasonable statistical parameters (Rtrain2 = 0.935, Rtest2 = 0.728 and QCV2 = 0.905). The established MD-SVR (molecular docking based SMV regression) model as well as model screening of a natural product database was carried out and two natural products (quercetin and myricetin) with good prediction activities were biologically evaluated. Both compounds exhibited promising B-RafV600E inhibitory activities (ICQuercetin50 = 7.59 μM and ICMyricetin50 = 1.56 μM), suggesting a high reliability and good applicability of the established MD-SVR model in the future development of B-RafV600E inhibitors with high efficacy.

Structural evidence of quercetin multi-target bioactivity: A reverse virtual screening strategy

The ubiquitous flavonoid quercetin is broadly recognized for showing diverse biological and health-promoting effects, such as anti-cancer, anti-inflammatory and cytoprotective activities. The therapeutic potential of quercetin and similar compounds for preventing such diverse oxidative stress-related pathologies has been generally attributed to their direct antioxidant properties. Nevertheless, accumulated evidence indicates that quercetin is also able to interact with multiple cellular targets influencing the activity of diverse signaling pathways. Even though there are a number of well-established protein targets such as phosphatidylinositol 3 kinase and xanthine oxidase, there remains a lack of a comprehensive knowledge of the potential mechanisms of action of quercetin and its target space. In the present work we adopted a reverse screening strategy based on ligand similarity (SHAFTS) and target structure (idTarget, LIBRA) resulting in a set of predicted protein target candidates. Furthermore, using this method we corroborated a broad array of previously experimentally tested candidates among the predicted targets, supporting the suitability of this screening approach. Notably, all of the predicted target candidates belonged to two main protein families, protein kinases and poly [ADP-ribose] polymerases. They also included key proteins involved at different points within the same signaling pathways or within interconnected signaling pathways, supporting a pleiotropic, multilevel and potentially synergistic mechanism of action of quercetin. In this context we highlight the value of quercetin's broad target profile for its therapeutic potential in diseases like inflammation, neurodegeneration and cancer.

Insight into molecular dynamics simulation of BRAF(V600E) and potent novel inhibitors for malignant melanoma

BRAF inhibitors have changed the standard therapeutic protocol for advanced or metastatic melanoma which harbored notorious BRAF(V600E) single mutation. However, drug resistance to BRAF inhibitors happens just like other cancer treatment. In this study, we constructed the ideal BRAF(V600E)-modeled structure through homology modeling and introduced the method of structure-based docking or virtual screening from the large compound database. Through certain methods of molecular dynamics simulation, we realized that BRAF(V600E) had quite prominent difference of molecular character or structural variation from the wild-type BRAF protein. It might confer the metamorphic character of advanced melanoma for the patients who harbored BRAF(V600E) mutation. By the methods of ligand-based quantitative structure-activity relationship and molecular dynamics simulation, we further recommend that aknadicine and 16beta-hydroxy-19s-vindolinine N-oxide from the traditional Chinese medicine are potent novel inhibitors for the management of malignant melanoma in the future.

In silico identification of novel kinase inhibitors by targeting B-Raf(v660e) from natural products database

The Ras/Raf/MEK/ERK (MAPK) signaling pathway has gained much attention from scientific community for therapeutic intervention in the past decades, specifically in oncology. Notably, a most prevalent B-Raf(v600e) mutant in Raf kinase family exhibits elevated kinase activity and results in constitutive activation of the MAPK pathway, thus making it a promising drug target for cancer therapy. Herein, virtual screening is applied to identify its potential inhibitors. Following the 25 ns molecular dynamic (MD) simulations, ZINC38541768, ZINC38541767, and ZINC12496469 are identified as B-Raf(v600e) potential inhibitors in a DFG-in conformation. Furthermore, according to the molecular mechanics/generalized born surface area (MM/GBSA) method, these three small molecules exhibit similar and good binding affinity toward B-Raf(v600e) (-38.76 kcal mol(-1), -42.60 kcal mol(-1), and -39.04 kcal mol(-1)). At the same time, several critical residues, such as I463, V471 in the P-loop, and DFG motif residue D594 within the A-loop, are also well clarified. All these results may not only indicate some future applications of inhibitors targeting B-Raf(v600e), but also benefit B-Raf(v600e) harboring cancer patients.

Hierarchical virtual screening approaches in small molecule drug discovery

Virtual screening has played a significant role in the discovery of small molecule inhibitors of therapeutic targets in last two decades. Various ligand and structure-based virtual screening approaches are employed to identify small molecule ligands for proteins of interest. These approaches are often combined in either hierarchical or parallel manner to take advantage of the strength and avoid the limitations associated with individual methods. Hierarchical combination of ligand and structure-based virtual screening approaches has received noteworthy success in numerous drug discovery campaigns. In hierarchical virtual screening, several filters using ligand and structure-based approaches are sequentially applied to reduce a large screening library to a number small enough for experimental testing. In this review, we focus on different hierarchical virtual screening strategies and their application in the discovery of small molecule modulators of important drug targets. Several virtual screening studies are discussed to demonstrate the successful application of hierarchical virtual screening in small molecule drug discovery.

SAR156497, an exquisitely selective inhibitor of aurora kinases

The Aurora family of serine/threonine kinases is essential for mitosis. Their crucial role in cell cycle regulation and aberrant expression in a broad range of malignancies have been demonstrated and have prompted intensive search for small molecule Aurora inhibitors. Indeed, over 10 of them have reached the clinic as potential anticancer therapies. We report herein the discovery and optimization of a novel series of tricyclic molecules that has led to SAR156497, an exquisitely selective Aurora A, B, and C inhibitor with in vitro and in vivo efficacy. We also provide insights into its mode of binding to its target proteins, which could explain its selectivity.

Astemizole arrests the proliferation of cancer cells by disrupting the EZH2-EED interaction of polycomb repressive complex 2

Polycomb Repressive Complex 2 (PRC2) modulates the chromatin structure and transcriptional repression by trimethylation lysine 27 of histone H3 (H3K27me3), a process that necessitates the protein-protein interaction (PPI) between the catalytic subunit EZH2 and EED. Deregulated PRC2 is intimately involved in tumorigenesis and progression, making it an invaluable target for epigenetic cancer therapy. However, until now, there have been no reported small molecule compounds targeting the EZH2-EED interactions. In the present study, we identified astemizole, an FDA-approved drug, as a small molecule inhibitor of the EZH2-EED interaction of PRC2. The disruption of the EZH2-EED interaction by astemizole destabilizes the PRC2 complex and inhibits its methyltransferase activity in cancer cells. Multiple lines of evidence have demonstrated that astemizole arrests the proliferation of PRC2-driven lymphomas primarily by disabling the PRC2 complex. Our findings demonstrate the chemical tractability of the difficult PPI target by a small molecule compound, highlighting the therapeutic promise for PRC2-driven human cancers via targeted destruction of the EZH2-EED complex.

Identifying novel selective non-nucleoside DNA methyltransferase 1 inhibitors through docking-based virtual screening

The DNA methyltransferases (DNMTs) found in mammals include DNMT1, DNMT3A, and DNMT3B and are attractive targets in cancer chemotherapy. DNMT1 was the first among the DNMTs to be characterized, and it is responsible for maintaining DNA methylation patterns. A number of DNMT inhibitors have been reported, but most of them are nucleoside analogs that can lead to toxic side effects and lack specificity. By combining docking-based virtual screening with biochemical analyses, we identified a novel compound, DC_05. DC_05 is a non-nucleoside DNMT1 inhibitor with low micromolar IC50 values and significant selectivity toward other AdoMet-dependent protein methyltransferases. Through a process of similarity-based analog searching, compounds DC_501 and DC_517 were found to be more potent than DC_05. These three potent compounds significantly inhibited cancer cell proliferation. The structure-activity relationship (SAR) and binding modes of these inhibitors were also analyzed to assist in the future development of more potent and more specific DNMT1 inhibitors.

Virtual screening strategies: recent advances in the identification and design of anti-cancer agents

Virtual screening (VS) is a well-established technique, which is now routinely employed in computer aided drug designing process. VS can be broadly classified into two categories, i.e., ligand-based and structure-based approach. In recent years, VS has emerged as a time saving and cost effective technique, capable of screening millions of compounds in a user friendly manner. In the area of cancer drug design, VS methods have been widely used and helped in identifying novel molecules as potential anti-cancer agents. Both ligand-based VS (LBVS) structure-based VS (SBVS) methods have been highly useful in the identification of a number of potential anti-cancer agents exhibiting activities in nanomolar range. In tune with the rapid progress in the enhancement of computational power, VS has witnessed significant change in terms of speed and hit rate and in future it is expected that VS will be a preferential alternative to high throughput screening (HTS). This review, discusses recent trends and contribution of VS in the area of anti-cancer drug discovery.

Structural optimization and biological screening of a steroidal scaffold possessing cucurbitacin-like functionalities as B-Raf inhibitors

Inhibition of the mitogen-activated protein kinase (MAPK) pathway by targeting the commonly occurring mutated B-Raf in melanoma has become a practical method for the development of drugs and drug candidates. In order to expand upon the currently reported structural scaffolds used to target the MAPK pathway, molecular docking studies led to the installation an α,β-unsaturated ketone side chain, related to the cucurbitacin class of natural products, on to an estrone core via an aldol condensation reaction, along with installation of the Δ(9,11) olefin to assemble what has been defined as a pseudo-cis configuration at the B/C ring juncture. Combination of these cucurbitacin-like features resulted in a compound with an enhanced biological profile against the A-375 mutant B-Raf cell line, in regards to their cytotoxicity and inhibitory activity toward phosphorylated extracellular-signal-regulated kinase (ERK).

Identification and synthesis of N-(thiophen-2-yl) benzamide derivatives as BRAF(V600E) inhibitors

The V600E BRAF kinase mutation, which activates the downstream MAPK signaling pathway, commonly occurs in about 8% of all human malignancies and about 50% of all melanomas. In this study, we employed virtual screening and chemical synthesis to identify a series of N-(thiophen-2-yl) benzamide derivatives as potent BRAF(V600E) inhibitors. Structure-activity relationship studies of these derivatives revealed that compounds b40 and b47 are the two most potent BRAF(V600E) inhibitors in this series.