The preprocessed initial files that feed the molecular dynamics (MD) simulation packages dramatically influence the outcome of the simulations. However, the popular MD simulation packages depend, to a great extent, on the user’s experience in the preparation of MD simulation systems. In this work, we present an easy-to-use tool called MDBuilder, a PyMOL plugin that assists researchers in building the starting structures for multiple popular MD simulation packages. MDBuilder is not only designed to assist MD beginners to overcome the steep learning curve by providing a menu-oriented, point-and-click user graphic interface (GUI), but also to provide an alternative way to prepare the input files for some highly scalable CHARMM force field-based MD simulation packages. The platform-independent GUI is implemented as a PyMOL plugin using the Python language, and it has been tested on Windows and Linux platforms. The source code and documentation of MDBuilder can be downloaded freely from https://github.com/HuiLiuCode/MDBuilder under the GNU General Public License.

The intricate complex system of the differentiation 47 (CD47) and the signal-regulatory protein alpha (SIRPα) cluster is a crucial target for cancer immunotherapy. Although the conformational state of the CD47-SIRPα complex has been revealed through crystallographic studies, further characterization is needed to fully understand the binding mechanism and to identify the hot spot residues involved. In this study, molecular dynamics (MD) simulations were carried out for the complexes of CD47 with two SIRPα variants (SIRPαv1, SIRPαv2) and the commercially available anti-CD47 monoclonal antibody (B6H12.2). The calculated binding free energy of CD47-B6H12.2 is lower than that of CD47-SIRPαv1 and CD47-SIRPαv2 in all the three simulations, indicating that CD47-B6H12.2 has a higher binding affinity than the other two complexes. Moreover, the dynamical cross-correlation matrix reveals that the CD47 protein shows more correlated motions when it binds to B6H12.2. Significant effects were observed in the energy and structural analyses of the residues (Glu35, Tyr37, Leu101, Thr102, Arg103) in the C strand and FG region of CD47 when it binds to the SIRPα variants. The critical residues (Leu30, Val33, Gln52, Lys53, Thr67, Arg69, Arg95, and Lys96) were identified in SIRPαv1 and SIRPαv2, which surround the distinctive groove regions formed by the B2C, C’D, DE, and FG loops. Moreover, the crucial groove structures of the SIRPα variants shape into obvious druggable sites. The C’D loops on the binding interfaces undergo notable dynamical changes throughout the simulation. For B6H12.2, the residues Tyr32_LC, His92_LC, Arg96_LC, Tyr32_HC, Thr52_HC, Ser53_HC, Ala101_HC, and Gly102_HC in its initial half of the light and heavy chains exhibit obvious energetic and structural impacts upon binding with CD47. The elucidation of the binding mechanism of SIRPαv1, SIRPαv2, and B6H12.2 with CD47 could provide novel perspectives for the development of inhibitors targeting CD47-SIRPα.

Glioma is a highly malignant primary brain tumor with a poor prognosis. Current treatments for intracranial glioma are often ineffective, necessitating the development of novel therapeutic agents. In this work, molecular docking-based screening analyses were conducted to identify dauricine as a dual-targeted agent of p53 and VEGFA by targeting the Loop1/Sheet3 (L1/S3) pocket of p53 and the Loop1/Loop3 (L1/L3) regions of VEGFA. The anticancer activity of dauricine was further evaluated using MTT, colony formation, wound-healing, transwell invasion, Western blot, and apoptosis assays, including Hoechst staining and flow cytometry on U87 and C6 glioma cell lines. A C6 xenograft model in BALB/c-nu mice was used to assess tumor growth inhibition. The in vivo anticancer effect of dauricine was detected by HE staining, and the levels of p53 and VEGFA were tested by IHC staining. The results showed that dauricine significantly inhibited the proliferation, migration, and invasion of glioma cells, induced apoptosis, and reduced tumor growth both in vitro and in vivo. Western blot analyses showed that dauricine upregulated p53 and downregulated VEGFA pathways. In vivo experiments demonstrated that dauricine inhibited the growth of subcutaneous tumors in nude mice by targeting p53 and VEGFA. Overall, these results demonstrated that dauricine suppresses glioma growth by targeting the p53 and VEGFA pathways, making it a promising anticancer agent for glioma treatment.