Huibin Wang

Bio: Huibin Wang is an academic researcher from Shenyang Pharmaceutical University. The author has contributed to research in topics: Virtual screening & Docking (molecular). The author has an hindex of 2, co-authored 6 publications receiving 5 citations.

Discovery of small molecule inhibitors through pharmacophore modeling, molecular docking, molecular dynamics simulation and experimental validation against myeloid cell leukemia-1 (Mcl-1).

Abstract: Myeloid cell leukemia-1 (Mcl-1) protein is a family of Bcl-2 (B cell lymphoma 2) rich proteases of the most common increase threshold for genetic aberrations observed in human cancer, including lung, breast, pancreatic, cervical, and ovarian cancers as well as leukemia and lymphoma. Mcl-1 is recognized as an attractive drug target in number of diseases, including cancer. In the present study we surveyed and collected queries compounds from PDB database of Mcl-1 protein and generated pharmacophore-based models adapted to screen the drug-like compounds from FDA approved database. The 206 best lead molecules from pharmacophore-screening were further evaluated by molecular docking, molecular dynamics simulation, MM-GBSA calculation, as well as experimental validation. Two hits, ZINC00601272 and ZINC00002166, showed the best docking scores, which showed a tendency to inhibit cell viability of HL60 and K562 leukemia cells with Mcl-1 expressions. Conclusively, the present study provides structural information of Mcl-1 inhibitors for next generations of cancer therapeutics through computational and experimental validation approach.Communicated by Ramaswamy H. Sarma.

Structural basis for tailor-made selective PI3K α/β inhibitors: a computational perspective

Abstract: PI3K α and β are Class IA PI3K isoforms that share a highly homologous ATP binding site, differing only in a few residues around the binding site. They are ubiquitously expressed in various organs and play many different roles in terms of mutations in carcinomas and signaling in tumor growth. Their pan-inhibitors should theoretically be effective against cancers by offering a potentially broader spectrum of activity, however, clinical development of most panPI3K inhibitors has discontinued probably owing to the problematic toxicities. Therefore, it is crucial to clarify the structural basis of the selective inhibition mechanism towards PI3K α and β. Towards this end, comprehensive computational approaches including molecular docking, molecular dynamics simulations, mutagenesis, and DFT technologies were applied to reveal the different interaction modes between highly selective PI3Kα and PI3Kβ inhibitors. It was found that the VAL851 of PI3Kα and VAL848 of PI3Kβ remarkably affected their selectivity by forming hydrogen bonds with different molecular scaffolds. Moreover, a diverse amino acid, GLN859 of PI3K α and ASP856 of PI3Kβ greatly contributed to distinguishing the inhibitory selectivity between PI3Kα and β. Of note, PI3Kβ seemed to form more water bridges with the surrounding water molecules. Collectively, these data shed light in depicting the PI3Kα/β selective mechanisms, which guided the future strategy for a rational design of selective inhibitors towards PI3Kα/β.

Comprehensive structure–activity relationship (SAR) investigation of C-aryl glycoside derivatives for the development of SGLT1/SGLT2 dual inhibitors

Abstract: Multi-combined computational approaches were used to explore the SAR and design novel potential SGLT1/SGLT2 dual inhibitors.

In silico strategy for isoform-selective 5-HT2AR and 5-HT2CR inhibitors

Abstract: 5-HT2AR and 5-HT2CR are widely expressed throughout the brain and have been drawing significant clinical interest due to their involvement in mediating mental disorders. Indeed, 5-HT2AR acts as a biological target for atypical antipsychotics and addiction, and 5-HT2CR also serves as a therapeutic target for depression and addiction. Given that 5-HT2AR and 5-HT2CR provide opposing influences upon DA mesocorticoaccumbens output, plus 5-HT2CR is thought to be involved in appetite that might result in the side effect of weight gain, it makes great sense for drug design to provide the selective mechanisms of 5-HT2AR and 5-HT2CR in order to meet the increasing need for more effective medications. Toward this end, the structure and chemical properties of crucial residues between 5-HT2AR and 5-HT2CR were analyzed based on their individual crystal structures. Moreover, pruvanserin and RS102221, the highly selective antagonists of 5-HT2AR and 5-HT2CR, respectively, were employed to illuminate the selective binding modes through a comprehensive application of in silico methods, including molecular docking, molecular dynamic simulations, MM-GBSA, alanine scanning mutagenesis, DFT technologies, and structure-based pharmacophore modeling. It was found that although 5-HT2A/CR isoforms share high sequence homology in active pockets, they do possess distinctive physiological functions. The key residues that contributed to the selectivity between 5-HT2A/CR are ASP155, LEU229, TRP336, and PHE340 of 5-HT2AR, as well as ASP134, LEU209, and PHE328 of 5-HT2CR. Moreover, in view of the much smaller hydrophobic region of the 5-HT2AR, a ligand with reduced side chain volume would increase its selectivity to 5-HT2AR, and vice versa. In addition, considering that RS102221/5-HT2CR formed more water bridges compared to that of pruvanserin/5-HT2AR, hydrogen bonding interactions should be emphasized in the design of 5-HT2CR selective inhibitors. Collectively, this study provided novel insights into the rational selectivity mechanisms of 5-HT2AR/5-HT2CR inhibitors, which laid important foundations for designing selective inhibitors towards 5-HT2AR and 5-HT2CR.

Docking study of chloroquine and hydroxychloroquine interaction with RNA binding domain of nucleocapsid phospho-protein - an in silico insight into the comparative efficacy of repurposing antiviral drugs.

Abstract: Recent outbreak of novel Coronavirus disease () pandemic around the world is associated with severe acute respiratory syndrome. The death toll associated with the pandemic is increasing day by day....

Application of Advanced Technologies in Natural Product Research: A Review with Special Emphasis on ADMET Profiling.

Abstract: The successful conversion of natural products (NPs) into lead compounds and novel pharmacophores has emboldened the researchers to harness the drug discovery process with a lot more enthusiasm. However, forfeit of bioactive NPs resulting from an overabundance of metabolites and their wide dynamic range have created the bottleneck in NP researches. Similarly, the existence of multidimensional challenges, including the evaluation of pharmacokinetics, pharmacodynamics, and safety parameters, has been a concerning issue. Advancement of technology has brought the evolution of traditional natural product researches into the computer-based assessment exhibiting pretentious remarks about their efficiency in drug discovery. The early attention to the quality of the NPs may reduce the attrition rate of drug candidates by parallel assessment of ADMET profiling. This article reviews the status, challenges, opportunities, and integration of advanced technologies in natural product research. Indeed, emphasis will be laid on the current and futuristic direction towards the application of newer technologies in early-stage ADMET profiling of bioactive moieties from the natural sources. It can be expected that combinatorial approaches in ADMET profiling will fortify the natural product-based drug discovery in the near future.

Computational study of quinoline-based thiadiazole compounds as potential antileishmanial inhibitors

Abstract: Leishmaniasis is a severe disease caused by protozoan parasites of the genus Leishmania and it is accountable for sizable morbidity and mortality worldwide.

Application of Molecular Simulation Methods in Food Science: Status and Prospects.

Abstract: Molecular simulation methods, such as molecular docking, molecular dynamic (MD) simulation, and quantum chemical (QC) calculation, have become popular as characterization and/or virtual screening tools because they can visually display interaction details that in vitro experiments can not capture and quickly screen bioactive compounds from large databases with millions of molecules. Currently, interdisciplinary research has expanded molecular simulation technology from computer aided drug design (CADD) to food science. More food scientists are supporting their hypotheses/results with this technology. To understand better the use of molecular simulation methods, it is necessary to systematically summarize the latest applications and usage trends of molecular simulation methods in the research field of food science. However, this type of review article is rare. To bridge this gap, we have comprehensively summarized the principle, combination usage, and application of molecular simulation methods in food science. We also analyzed the limitations and future trends and offered valuable strategies with the latest technologies to help food scientists use molecular simulation methods.