Structure based pharmacophore study to identify possible natural selective PARP-1 trapper as anti-cancer agent

Synthetically accessible de novo design using reaction vectors: Application to PARP1 inhibitors

De novo design has been a hotly pursued topic for many years. Most recent developments have involved the use of deep learning methods for generative molecular design. Despite increasing levels of algorithmic sophistication, the design of molecules that are synthetically accessible remains a major challenge. Reaction-based de novo design takes a conceptually simpler approach and aims to address synthesisability directly by mimicking synthetic chemistry and driving structural transformations by known reactions that are applied in a stepwise manner. However, the use of a small number of hand-coded transformations restricts the chemical space that can be accessed and there are few examples in the literature where molecules and their synthetic routes have been designed and executed successfully. Here we describe the application of reaction-based de novo design to the design of synthetically accessible and biologically active compounds as proof-of-concept of our reaction vector-based software. Reaction vectors are derived automatically from known reactions and allow access to a wide region of synthetically accessible chemical space. The design was aimed at producing molecules that are active against PARP1 and which have improved brain penetration properties compared to existing PARP1 inhibitors. We synthesised a selection of the designed molecules according to the provided synthetic routes and tested them experimentally. The results demonstrate that reaction vectors can be applied to the design of novel molecules of biological relevance that are also synthetically accessible.

A universal programmable Gaussian boson sampler for drug discovery

Gaussian boson sampling (GBS) has the potential to solve complex graph problems, such as clique finding, which is relevant to drug discovery tasks. However, realizing the full benefits of quantum enhancements requires large-scale quantum hardware with universal programmability. Here we have developed a time-bin-encoded GBS photonic quantum processor that is universal, programmable and software-scalable. Our processor features freely adjustable squeezing parameters and can implement arbitrary unitary operations with a programmable interferometer. Leveraging our processor, we successfully executed clique finding on a 32-node graph, achieving approximately twice the success probability compared to classical sampling. As proof of concept, we implemented a versatile quantum drug discovery platform using this GBS processor, enabling molecular docking and RNA-folding prediction tasks. Our work achieves GBS circuitry with its universal and programmable architecture, advancing GBS toward use in real-world applications.

In-silico method for elucidation of prodigiosin as PARP-1 inhibitor a prime target of Triple-negative breast cancer

Triple-Negative Breast Cancer (TNBC) is found to be one of the life-threatening cancer. Poly (ADP-Ribose) Polymerase-1 (PARP-1) is overexpressed by those tumour cells, which become resistant to chemotherapies. Inhibition of PARP-1 has a considerable effect on treating TNBC. Prodigiosin is a valuable pharmaceutical compound that exhibits anticancer properties. The present study aims to virtually evaluate prodigiosin as a potent PARP-1 inhibitor using Molecular docking and Molecular Dynamics (MD) simulation studies. The PASS (Prediction of Activity Spectra for Substances) prediction tool evaluated the biological properties of prodigiosin. Then the drug-likeness and pharmacokinetic properties of prodigiosin were determined using Swiss-ADME software. It was suggested that prodigiosin obeyed Lipinski's rule of five and thus could act as a drug with good pharmacokinetic properties. Moreover, molecular docking was done with AutoDock 4.2 to identify the critical amino acids of the protein-ligand complex. It was indicated that prodigiosin has a docking score of -8.08 kcal/mol, which showed its effective interaction with crucial amino acid, His201A of PARP-1 protein. Further, MD simulation was performed using Gromacs software to validate the stability of the prodigiosin-PARP-1 complex. Prodigiosin was found to have good structural stability and affinity at the active site of PARP-1 protein. Additionally, PCA and MM-PBSA were calculated for the prodigiosin-PARP-1 complex, which revealed that prodigiosin has an excellent binding affinity towards PARP-1 protein. Prodigiosin can possibly be used as oral drug due to its PARP-1 inhibition through high binding affinity, structural stability, and receptor flexibility towards crucial amino acid residue His201A of PARP-1 protein. In-addition, in-vitro cytotoxicity, and apoptosis analysis of prodigiosin-treated TNBC cell line-MDA-MB-231 revealed that prodigiosin exhibited significant anticancer activity in 101.1 µg/mL concentration, when compared to commercially available synthetic drug cisplatin. Thus, prodigiosin could act as a potential candidate for treatment of TNBC than the commercially available synthetic drugs.

An overview of compound properties, multiparameter optimization, and computational drug design methods for PARP-1 inhibitor drugs

Breast cancer treatment with PARP-1 inhibitors remains challenging due to emerging toxicities, drug resistance, and unaffordable costs of treatment options. How do we invent strategies to design better anti-cancer drugs? A part of the answer is in optimized compound properties, desirability functions, and modern computational drug design methods that drive selectivity and toxicity and have not been reviewed for PARP-1 inhibitors. Nonetheless, comparisons of these compound properties for PARP-1 inhibitors are not available in the literature. In this review, we analyze the physchem, PKPD space to identify inherent desirability functions characteristic of approved drugs that can be valuable for the design of better candidates. Recent literature utilizing ligand, structure-based drug design strategies and matched molecular pair analysis (MMPA) for the discovery of novel PARP-1 inhibitors are also reviewed. Thus, this perspective provides valuable insights into the medchem and multiparameter optimization of PARP-1 inhibitors that might be useful to other medicinal chemists.

In Vitro Antibacterial Activity and in Silico Analysis of the Bioactivity of Major Compounds Obtained from the Essential Oil of Virola surinamensis Warb (Myristicaceae)

Essential oils are well known for their antimicrobial activity and they are used as an effective food preservative. Virola is one of the five genera of Myristicaceae and this genus is native to the American continent, especially in neotropical regions. The largest number of species of this genus is found in the Amazon region and the most important species include Virola surinamensis Warb. and Virola sebifera Aubl. In the present study, we describe the chemical composition of the essential oil of the V. surinamensis obtained at two different periods of the day in two seasons (rainy and dry), as well as their antimicrobial activity against pathogenic bacterial strains of Pseudomonas aeruginosa, Escherichia coli, and Staphylococcus aureus. In addition, we investigated, using in silico tools, the antimicrobial activity of the major chemical compounds present in the essential oil of V. surinamensis. The samples collected at different seasons and times showed a similar chemical profile, characterized by the major constituents α-pinene (>33%) and β-pinene (>13%). The essential oil of V. surinamensis showed an interesting antibacterial activity, exhibiting low inhibitory concentrations against the tested bacterial species. The computational investigation indicated that limonene, myrcene, and β-pinene could be related to the antibacterial activity against the tested pathogenic bacterial strains. Our results shed light on the possible constituents of essential oil that could be related to its activity against bacterial species and might be useful for further experimental tests that aim to discover new potential antibacterial agents for food preservation.

DCLK1 and its interaction partners: An effective therapeutic target for colorectal cancer

Doublecortin-like kinase protein 1 (DCLK1) is a microtubule-associated protein with a C-terminal serine/threonine kinase domain. Its expression was first reported in radial glial cells, where it serves an essential role in early neurogenesis, and since then, other functions of the DCLK1 protein have also been identified. Initially considered to be a marker of quiescent gastrointestinal and pancreatic stem cells, DCLK1 has recently been identified in the gastrointestinal tract as a marker of tuft cells. It has also been implicated in different types of cancer, where it regulates several vital pathways, such as Kras signaling. However, its underlying molecular mechanisms remain unclear. The present review discusses the different roles of DCLK1 and its interactions with other proteins that are homologically similar to DCLK1 to develop a novel therapeutic strategy to target cancer cells more accurately.

Computational investigation of FDA approved drugs as selective PARP-1 inhibitors by targeting BRCT domain for cancer therapy

Poly(ADP-ribose) polymerase-1 is a promising target for the treatment of cancer due to its involvement in base excision repair pathways for repairing DNA single-strand breaks. However, available PARP-1 inhibitors target a highly conserved PARPs catalytic domain, which causes toxicity due to the off-target activity. Therefore, the present study was hypothesized to identify selective inhibitors by targeting specific protein-protein interacting (PPI) PARP-1 BRCT domain. Moreover, PPI hotspot residues (Gly399, Lys400, Leu401, Lys441 & Lys442) and a druggable pocket was detected to screen small molecule inhibitors. Hence, two FDA approved drug molecules (levoleucovorin and balsalazide) were recognized to fit in the druggable pocket. Since they are already under investigation for anti-cancer activity, thus could be further explored in PARP-1 sensitive cancer cells to expand their selectivity and develop as effective anti-cancer agents. Besides, the study also provides detailed structural insight of PARP-1 and XRCC1 complex through their BRCT domains.

Identification of novel inhibitor of protein tyrosine phosphatases delta: structure-based pharmacophore modeling, virtual screening, flexible docking, molecular dynamics simulation, and post-molecular dynamics analysis

Owing to their unique functions in regulating the synapse activity of protein tyrosine phosphatases delta (PTPδ) that has drawn special attention for developing drugs to autism spectrum disorders (ASDs). In this study, the PTPδ pharmacophore was first established by the structure-based pharmacophore method. Subsequently, 10 compounds contented Lipinski's rule of five was acquired by the virtual screening of the PTPδ pharmacophore against ZINC and PubChem databases. Then, the 10 identified molecules were discovered that had better binding affinity than a known PTPδ inhibitors compound SCHEMBL16375396. Two compounds SCHEMBL16375408 and ZINC19796658 with high binding score, low toxicity were gained. They were observed by docking analysis and molecular dynamics simulations that the novel potential inhibitors not only possessed the same function as SCHEMBL16375396 did in inhibiting PTPδ, but also had more favorable conformation to bind with the catalytic active regions. This study provides a new method for identify PTPδ inhibitor for the treatment of ASDs disease.Communicated by Ramaswamy H. Sarma.