Discovery and design of dual inhibitors targeting Sphk1 and Sirt1.

CONTEXT: Leukaemia has become a serious threat to human health. Although tyrosine kinase inhibitors (TKIs) have been developed as targets for the remedy of leukaemia, drug resistance occurs. Research demonstrated that the simultaneous targeting of sphingosine kinase 1 (Sphk1) and Sirtuin 1 (Sirt1) can downregulate myeloid cell leukaemia-1 (MCL-1), overcome the resistance of tyrosine kinase inhibitors, and play a synergistic inhibitory impact on leukaemia treatment. METHODS: In this study, virtual screening of 7.06 million small molecules was done by sphingosine kinase 1 and Sirtuin 1 pharmacophore models using Schrödinger version 2019; after that, ADME and Toxicity molecule properties were predicted using Discovery Studio. Molecular docking using Schrödinger selected five molecules, which have the best binding affinity with sphingosine kinase 1 and Sirtuin 1. The five molecules and reference inhibitors were constructed with a total of 12 systems with GROMACS that carried out 100 ns molecular dynamics simulation and molecular mechanics/Poisson-Boltzmann surface area (MM/PBSA) calculation. Due to compound 3 has the lowest binding energy, its structure was modified. A series of compounds docked with sphingosine kinase 1 and Sirtuin 1, respectively. Among them, QST-LC03, QST-LD05, QST-LE03, and QST-LE04 have the better binding affinity than reference inhibitors. Moreover, the SwissADME and PASS platforms predict that 1, 3, QST-LC03, and QST-LE04 have further study value.

De novo design of dual-target JAK2, SMO inhibitors based on deep reinforcement learning, molecular docking and molecular dynamics simulations.

Triple-negative breast cancer (TNBC) and HER2-positive breast cancer are particularly aggressive and the effectiveness of current therapies for them is limited. TNBC lacks effective therapies and HER2-positive cancer is often resistant to HER2-targeted drugs after an initial response. The recent studies have demonstrated that the combination of JAK2 inhibitors and SMO inhibitors can effectively inhibit the growth and metastasis of TNBC and HER2-positive drug resistant breast cancer cells. In this study, deep reinforcement learning was used to learn the characteristics of existing small molecule inhibitors of JAK2 and SMO, and to generate a novel library of small molecule compounds that may be able to inhibit both JAK2 and SMO. Subsequently, the molecule library was screened by molecular docking and a total of 7 compounds were selected out as dual inhibitors of JAK2 and SMO. Molecular dynamics simulations and binding free energies showed that the top three compounds stably bound to both JAK2 and SMO proteins. The binding free energies and hydrogen bond occupancy of key amino acids indicate that A8976 and A10625 has good properties and could be a potential dual-target inhibitor of JAK2 and SMO.

Virtual screening and molecular dynamics simulation for identification of natural antiviral agents targeting SARS-CoV-2 NSP10.

New variations of SARS-CoV-2 continue to emerge in the global pandemic, which may be resistant to at least some vaccines in COVID-19, indicating that drug and vaccine development must be continuously strengthened. NSP10 plays an essential role in SARS-CoV-2 viral life cycle. It stimulates the enzymatic activities of NSP14-ExoN and NSP16-O-MTase by the formation of NSP10/NSP14 and NSP10/NSP16 complexes. Inhibiting NSP10 can block the binding of NSP10 to NSP14 and NSP16. This study has identified potential natural NSP10 inhibitors from ZINC database. The protein druggable pocket was identified for screening candidates. Molecular docking of the selected compounds was performed and MM-GBSA binding energy was calculated. After ADMET assessment, 4 hits were obtained for favorable druggability. The analysis of site interactions suggested that the hits all had excellent binding. Molecular dynamics studies revealed that selected natural compounds stably bind to NSP10. These compounds were identified as potential leads against NSP10 for the development of strategies to combat SARS-CoV-2 replication and could serve as the basis for further studies.

Design of SARS-CoV-2 Mpro, PLpro dual-target inhibitors based on deep reinforcement learning and virtual screening.

Background: Since December 2019, SARS-CoV-2 has continued to spread rapidly around the world. The effective drugs may provide a long-term strategy to combat this virus. The main protease (Mpro) and papain-like protease (PLpro) are two important targets for the inhibition of SARS-CoV-2 virus replication and proliferation. Materials & methods: In this study, deep reinforcement learning, covalent docking and molecular dynamics simulations were used to identify novel compounds that have the potential to inhibit both Mpro and PLpro. Results & conclusion: Three compounds were identified that can effectively occupy the Mpro protein cavity with the PLpro protein cavity and form high-frequency contacts with key amino acid residues (Mpro: His41, Cys145, Glu166; PLpro: Cys111). These three compounds can be further investigated as potential lead compounds for SARS-CoV-2 inhibitors.

Identification of inhibitors targeting HIF-2α/c-Myc by molecular docking and MM-GBSA technology.

The treatment of ccRCC by targeting hypoxia-inducible factor HIF-2α is currently a direct and effective method. Studies have shown that HIF-2α and c-Myc cooperate to promote ccRCC tumor progression, and the overexpression of c-Myc is related to the progress and drug resistance of most human cancers. Although HIF-2α and c-Myc are important drug targets, their dual inhibitors are still lacking. We used virtual screening tools (mainly including molecular docking and MM-GBSA technology) to obtain some well-listed compounds that can potentially target HIF-2α and c-Myc and used molecular dynamics simulations to study their binding with these protein systems. Using a structure-based screening scheme, a batch of top-ranking compounds were selected, and their binding affinities were predicted of these compounds were performed. Representative compound C93106, C43257, and C41580 all showed good comprehensive binding score. Our results indicate that the target compounds can all form key interactions with the active site of the protein, and 30 ns molecular dynamic simulation of the complex system indicates a stable binding conformation. This research laid the foundation for the development of more effective and specific HIF-2α and c-Myc dual-target inhibitors.

Design and screening of FAK, CDK 4/6 dual inhibitors by pharmacophore model, molecular docking, and molecular dynamics simulation.

Focal adhesion kinase (FAK) is one kind of tyrosine kinases that modulates integrin and growth factor signaling pathways, which is a promising therapeutic target because of involving in the migration, proliferation and survival of cancer cell. Overexpression and amplification of cyclin-dependent kinase 4/6 (CDK4/6) occur in many cancers and may be the cause of resistance to CDK4/6 inhibitors in preclinical models. The latest research shows that the combination of FAK and CDK4/6 can be dually targeted to enhance the antitumor effects. In this study, FAK and CDK4/6 dual target inhibitors were designed by computer-aided drug design. Seven million molecules were screened by the pharmacophore model and molecular docking. Finally, 6 compounds were obtained. Molecular dynamics simulation of compound 1, 2 and 3 showed that it has good binding stability to both receptors. According to the binding modes of compound 1 with two receptors, corresponding modifications were made, and 7 novel designed compounds were obtained. The docking energy of these novel designed compounds were lower than that of compound 1, and they can be tested in future.Communicated by Ramaswamy H. Sarma.

De novo design of VEGFR-2 tyrosine kinase inhibitors based on a linked-fragment approach.

Vascular endothelial growth factor receptor-2 (VEGFR-2) tyrosine kinase inhibitors have been demonstrated to possess substantial antitumor activity. VEGFR-2 tyrosine kinase inhibitors are crucial for development of antitumor drugs. Based on the crystal structure of VEGFR-2 tyrosine kinase, a linked-fragment strategy was employed to design novel VEGFR-2 tyrosine kinase inhibitors, and 1000 compounds were generated in this process. Absorption, distribution, metabolism, excretion and toxicity (ADMET) were used to screen the 1000 compounds, and 59 compounds were acceptable. Scaffold hopping was then used for further screening, and only four compounds were obtained in this way. Then, the binding energy of the four molecules to VEGFR-2 tyrosine kinase was calculated using molecular docking, and their values were found to be lower than that of Sorafenib. Finally, molecular dynamics simulations were performed on the complex of the compound with the lowest binding energy with VEGFR-2 tyrosine kinase, and the binding model was analyzed. At the end, four chemical entities with novel structures were obtained, and were suggested for experimental testing in future studies.

QSAR and molecular docking studies on oxindole derivatives as VEGFR-2 tyrosine kinase inhibitors.

The three-dimensional quantitative structure-activity relationships (3D-QSAR) were established for 30 oxindole derivatives as vascular endothelial growth factor receptor-2 (VEGFR-2) tyrosine kinase inhibitors by using comparative molecular field analysis (CoMFA) and comparative similarity indices analysis comparative molecular similarity indices analysis (CoMSIA) techniques. With the CoMFA model, the cross-validated value (q(2)) was 0.777, the non-cross-validated value (R(2)) was 0.987, and the external cross-validated value ([Formula: see text]) was 0.72. And with the CoMSIA model, the corresponding q(2), R(2) and [Formula: see text] values were 0.710, 0.988 and 0.78, respectively. Docking studies were employed to bind the inhibitors into the active site to determine the probable binding conformation. The binding mode obtained by molecular docking was in good agreement with the 3D-QSAR results. Based on the QSAR models and the docking binding mode, a set of new VEGFR-2 tyrosine kinase inhibitors were designed, which showed excellent predicting inhibiting potencies. The result revealed that both QSAR models have good predictive capability to guide the design and structural modification of homologic compounds. It is also helpful for further research and development of new VEGFR-2 tyrosine kinase inhibitors.

The unbinding studies of vascular endothelial growth factor receptor-2 protein tyrosine kinase type II inhibitors.

Vascular endothelial growth factor receptor-2 (VEGFR-2) tyrosine kinase has two conformations, active and inactive conformations. Type II inhibitors bind to inactive conformation. It has two possible binding/unbinding paths. To explore the unbinding path of inhibitor 01-435 that was generated by fragment build in the binding pocket of VEGFR-2, molecular dynamics (MD) simulation was performed on the crystal structure of VEGFR-2 in complex with 01-435, then steered molecular dynamics (SMD) simulation was executed on the crystal structure of VEGFR-2 in complex with 01-435. Pull force, van der Waals and electrostatic interaction along the two paths were calculated by using SMD simulation. The SMD simulation results indicate that the more favorable path for inhibitor dissociation is along with the traditional ATP-channel rather than the allosteric-pocket-channel, which is mainly due to the less electrostatic interaction that the ligand suffers during dissociation process along the traditional ATP-channel.

A novel approach to cloning and expression of human thymidylate synthase.

Thymidylate synthase (TS) catalyzes the transfer of a methyl group from methylenetetrahydrofolate to dUMP to form dTMP. It is a primary target in the chemotherapy of colorectal cancers and some other neoplasms. In order to obtain pure protein for analysis of structure and biological function, an expression vector TS-pET28b (+) was constructed by inserting wild-type human thymidylate synthase (hTS) cDNA into pET28b (+). Then an expression strain was selected after transformation of the recombined plasmid into Rosetta (DE3). Fusion protein with His-tag was efficiently expressed in the form of inclusion bodies after IPTG induction and the content was approximately 40.0% of total bacteria proteins after optimizing expression conditions. When inclusion bodies were washed, dissolved and purified by Ni-NTA under denatured conditions, the purity was up to 90%. On SDS-PAGE and West-blotting, the protein band was found to match well with the predicted relative molecular mass-36kDa. Bioactivity was 0.1 U/mg. The results indicated that high-level expression of wild-type hTS cDNA can be achieved in prokaryotes with our novel method, facilitating research into related chemotherapy.

Refinement and 3D-QSAR Studies of Inhibitors of Cyclophilin A Containing Amide Linker.

Cyclophilin A (CypA) is a ubiquitous cellular enzyme playing essential role in many biological processes, and the discovery of CypA inhibitor is now of special interest in the treatment of immunological disorders. In this work, molecular modeling studies were performed to develop a predictive Common Pharmacophore Hypothesis (CPH) and use it for alignment in 3D-QSAR studies using CoMFA and CoMSIA. A total of 30 compounds containing an amide fragment as the key linker, consisting of 17 of our previously discovered CypA inhibitors and 13 other inhibitors reported in the literature, were selected for pharmacophore refinement and 3D-QSAR studies. The best pharmacophore hypothesis AADR, which had two hydrogen bond acceptors, a hydrogen bond donor, and an aromatic ring, was obtained and used for the alignment of molecules in CoMFA and CoMSIA model development. The models showed a good r 2 value of 0.992 and 0.949 for CoMFA and CoMSIA, respectively. The contour maps of the models were analyzed to give structural insight for activity improvement of future novel CypA inhibitors. The CPH can also provide a powerful template for virtual screening and design of new CypA inhibitors.

Primary antioxidant free radical scavenging and redox signaling pathways in higher plant cells.

Antioxidants in plant cells mainly include glutathione, ascorbate, tocopherol, proline, betaine and others, which are also information-rich redox buffers and important redox signaling components that interact with cellular compartments. As an unfortunate consequence of aerobic life for higher plants, reactive oxygen species (ROS) are formed by partial reduction of molecular oxygen. The above enzymatic and non-enzymatic antioxidants in higher plant cells can protect their cells from oxidative damage by scavenging ROS. In addition to crucial roles in defense system and as enzyme cofactors, antioxidants influence higher plant growth and development by modifying processes from miotosis and cell elongation to senescence and death. Most importantly, they provide essential information on cellular redox state, and regulate gene expression associated with biotic and abiotic stress responses to optimize defense and survival. An overview of the literature is presented in terms of primary antioxidant free radical scavenging and redox signaling in plant cells. Special attention is given to ROS and ROS-anioxidant interaction as a metabolic interface for different types of signals derived from metabolisms and from the changing environment. This interaction regulates the appropriate induction of acclimation processes or execution of cell death programs, which are the two essential directions for higher plant cells.

N-methylformamide-benzene complex as a prototypical peptide N-H...pi hydrogen-bonded system: density functional theory and MP2 studies.

Although the existence of peptide N-H...pi hydrogen bonds recently has been reported in protein structures, little is known about their strength and binding nature and, therefore, the relative importance of the interaction. To shed light on this binding, the N-methylformamide-benzene complex, as a model of the peptide N-H...pi hydrogen bonding, was studied by using density functional theory and Møller-Plesset second-order perturbation (MP2) methods. The geometry of the complex was fully optimized at the B3LYP/6-31G(d,p) and MP2/6-31G(d,p) levels. The optimized interaction distances are about 3.6 and 3.2 A, respectively, at the two levels. The binding energy corrected by basis set superposition error with the MP2/cc-pVTZ method based on the MP2/6-31G geometry is -4.37 kcal/mol, which is as strong as the conventional hydrogen bonding. The calculated results suggest that the peptide N-H...pi hydrogen bonding is of sufficient strength to play an important role in the stabilization of protein structures. These results are helpful to better understand the characteristics and nature of the peptide N-H...pi interaction as well as to modify current force fields to better represent this special interaction.