Virtual screening of potential anticancer drugs based on microbial products

Potentials and future perspectives of multi-target drugs in cancer treatment: the next generation anti-cancer agents

Cancer is a major public health problem worldwide with more than an estimated 19.3 million new cases in 2020. The occurrence rises dramatically with age, and the overall risk accumulation is combined with the tendency for cellular repair mechanisms to be less effective in older individuals. Conventional cancer treatments, such as radiotherapy, surgery, and chemotherapy, have been used for decades to combat cancer. However, the emergence of novel fields of cancer research has led to the exploration of innovative treatment approaches focused on immunotherapy, epigenetic therapy, targeted therapy, multi-omics, and also multi-target therapy. The hypothesis was based on that drugs designed to act against individual targets cannot usually battle multigenic diseases like cancer. Multi-target therapies, either in combination or sequential order, have been recommended to combat acquired and intrinsic resistance to anti-cancer treatments. Several studies focused on multi-targeting treatments due to their advantages include; overcoming clonal heterogeneity, lower risk of multi-drug resistance (MDR), decreased drug toxicity, and thereby lower side effects. In this study, we'll discuss about multi-target drugs, their benefits in improving cancer treatments, and recent advances in the field of multi-targeted drugs. Also, we will study the research that performed clinical trials using multi-target therapeutic agents for cancer treatment.

In silico investigation of cholesterol-lowering drugs to find potential inhibitors of dehydrosqualene synthase in Staphylococcus aureus

Staphylococcus aureus is a lethal pathogen that can cause various bacterial infections. This study targets the CrtM enzyme of S. aureus, which is crucial for synthesizing golden carotenoid pigment: staphyloxanthin, which provides anti-oxidant activity to this bacterium for combating antimicrobial resistance inside the host cell. The present investigation quests for human SQS inhibitors against the CrtM enzyme by employing structure-based drug design approaches including induced fit docking (IFD), molecular dynamic (MD) simulations, and binding free energy calculations. Depending upon the docking scores, two compounds, lapaquistat acetate and squalestatin analog 20, were identified as the lead molecules exhibit higher affinity toward the CrtM enzyme. These docked complexes were further subjected to 100 ns MD simulation and several thermodynamics parameters were analyzed. Further, the binding free energies (ΔG) were calculated for each simulated protein-ligand complex to study the stability of molecular contacts using the MM-GBSA approach. Pre-ADMET analysis was conducted for systematic evaluation of physicochemical and medicinal chemistry properties of these compounds. The above study suggested that lapaquistat acetate and squalestatin analog 20 can be selected as potential lead candidates with promising binding affinity for the S. aureus CrtM enzyme. This study might provide insights into the discovery of potential drug candidates for S. aureus with a high therapeutic index.

Supplementary Information

The online version contains supplementary material available at 10.1007/s13205-023-03862-y.

Discovery of selective and potent USP22 inhibitors via structure-based virtual screening and bioassays exerting anti-tumor activity

Ubiquitin-specific protease 22 (USP22) plays a prominent role in tumor development, invasion, metastasis and immune reprogramming, which has been proposed as a potential therapeutic target for cancer. Herein, we employed a structure-based discovery and biological evaluation and discovered that Rottlerin (IC50 = 2.53 μM) and Morusin (IC50 = 8.29 μM) and as selective and potent USP22 inhibitors. Treatment of HCT116 cells and A375 cells with each of the two compounds resulted in increased monoubiquitination of histones H2A and H2B, as well as reduced protein expression levels of Sirt1 and PD-L1, all of which are known as USP22 substrates. Additionally, our study demonstrated that the administration of Rottlerin or Morusin resulted in an increase H2Bub levels, while simultaneously reducing the expression of Sirt1 and PD-L1 in a manner dependent on USP22. Furthermore, Rottlerin and Morusin were found to enhance the degradation of PD-L1 and Sirt1, as well as increase the polyubiquitination of endogenous PD-L1 and Sirt1 in HCT116 cells. Moreover, in an in vivo syngeneic tumor model, Rottlerin and Morusin exhibited potent antitumor activity, which was accompanied by an enhanced infiltration of T cells into the tumor tissues. Using in-depth molecular dynamics (MD) and binding free energy calculation, conserved residue Leu475 and non-conserved residue Arg419 were proven to be crucial for the binding affinity and inhibitory function of USP22 inhibitors. In summary, our study established a highly efficient approach for USP22-specific inhibitor discovery, which lead to identification of two selective and potent USP22 inhibitors as potential drugs in anticancer therapy.

Design and Identification of a Novel Antiviral Affinity Peptide against Fowl Adenovirus Serotype 4 (FAdV-4) by Targeting Fiber2 Protein

Outbreaks of hydropericardium hepatitis syndrome caused by fowl adenovirus serotype 4 (FAdV-4) with a novel genotype have been reported in China since 2015, with significant economic losses to the poultry industry. Fiber2 is one of the important structural proteins on FAdV-4 virions. In this study, the C-terminal knob domain of the FAdV-4 Fiber2 protein was expressed and purified, and its trimer structure (PDB ID: 7W83) was determined for the first time. A series of affinity peptides targeting the knob domain of the Fiber2 protein were designed and synthesized on the basis of the crystal structure using computer virtual screening technology. A total of eight peptides were screened using an immunoperoxidase monolayer assay and RT-qPCR, and they exhibited strong binding affinities to the knob domain of the FAdV-4 Fiber2 protein in a surface plasmon resonance assay. Treatment with peptide number 15 (P15; WWHEKE) at different concentrations (10, 25, and 50 μM) significantly reduced the expression level of the Fiber2 protein and the viral titer during FAdV-4 infection. P15 was found to be an optimal peptide with antiviral activity against FAdV-4 in vitro with no cytotoxic effect on LMH cells up to 200 μM. This study led to the identification of a class of affinity peptides designed using computer virtual screening technology that targeted the knob domain of the FAdV-4 Fiber2 protein and may be developed as a novel potential and effective antiviral strategy in the prevention and control of FAdV-4.

A comprehensive review on recent approaches for cancer drug discovery associated with artificial intelligence

Through the revolutionization of artificial intelligence (AI) technologies in clinical research, significant improvement is observed in diagnosis of cancer. Utilization of these AI technologies, such as machine and deep learning, is imperative for the discovery of novel anticancer drugs and improves existing/ongoing cancer therapeutics. However, building a model for complicated cancers and their types remains a challenge due to lack of effective therapeutics that hinder the establishment of effective computational tools. In this review, we exploit recent approaches and state-of-the-art in implementing AI methods for anticancer drug discovery, and discussed how advances in these applications need to be considered in the current cancer therapeutics. Considering the immense potential of AI, we explore molecular docking and their interactions to recognize metabolic activities that support drug design. Finally, we highlight corresponding strategies in applying machine and deep learning methods to various types of cancer with their pros and cons.