3D- and 2D-QSAR models' study and molecular docking of novel nitrogen-mustard compounds for osteosarcoma.

Background: The dipeptide-alkylated nitrogen-mustard compound is a new kind of nitrogen-mustard derivative with a strong anti-tumor activity, which can be used as a potential anti-osteosarcoma chemotherapy drug. Objective: 2D- and 3D-QSAR (structure-activity relationship quantification) models were established to predict the anti-tumor activity of dipeptide-alkylated nitrogen-mustard compounds. Method: In this study, a linear model was established using a heuristic method (HM) and a non-linear model was established using the gene expression programming (GEP) algorithm, but there were more limitations in the 2D model, so a 3D-QSAR model was introduced and established through the CoMSIA method. Finally, a series of new dipeptide-alkylated nitrogen-mustard compounds were redesigned using the 3D-QSAR model; docking experiments were carried out on several compounds with the highest activity against tumors. Result: The 2D- and 3D-QSAR models obtained in this experiment were satisfactory. A linear model with six descriptors was obtained in this experiment using the HM through CODESSA software, where the descriptor "Min electroph react index for a C atom" has the greatest effect on the compound activity; a reliable non-linear model was obtained using the GEP algorithm model (the best model was generated in the 89th generation cycle, with a correlation coefficient of 0.95 and 0.87 for the training and test set, respectively, and a mean error of 0.02 and 0.06, respectively). Finally, 200 new compounds were designed by combining the contour plots of the CoMSIA model with each other, together with the descriptors in the 2D-QSAR, among which compound I1.10 had a high anti-tumor and docking ability. Conclusion: Through the model established in this study, the factors influencing the anti-tumor activity of dipeptide-alkylated nitrogen-thaliana compounds were revealed, providing direction and guidance for the further design of efficient chemotherapy drugs against osteosarcoma.

Tit Structure-activity Relationship Study and Design of Novel 1, 8- Naphthimide Derivatives as Potential DNA-targeting Chemotherapeutic Agents for Osteosarcoma.

BACKGROUND: 1, 8-naphthimide is a novel tumor inhibitor targeting nuclear DNA, which makes it applicable to the design and development of anti-osteosarcoma drugs. OBJECTIVE: The aim of this study is to establish a satisfactory model based on 1, 8-naphthimide derivatives that makes reliable prediction as DNA-targeted chemotherapy agents for osteosarcoma. METHODS: All compounds are constructed using ChemDraw software and subsequently optimized using Sybyl software. COMSIA method is used to construct QSAR model with the optimized compound in Sybyl software package. A series of new 1, 8-naphthalimide derivatives are designed and their IC50 values are predicted using the QSAR model. Finally, the newly designed compounds are screened according to IC50 values, and molecular docking experiments are conducted on the top ten compounds of IC50. RESULTS: The COMSIA model shows that q2 is 0.529 and the optimum number of components is 6. The model has a high r2 value of 0.993 and a low SEE of 0.033, with the F value and the r2 predicted to be 495.841 and 0.996 respectively. The statistical results and verification results of the model are satisfactory. In addition, analyzing the contour maps is conducive to finding the structural requirements. CONCLUSION: The results of this study can provide guidance for medical chemists and other related workers to develop targeted chemotherapy drugs for osteosarcoma.

QSAR Study of Novel 1, 8-Naphthimide Derivatives Targeting Nuclear DNA.

BACKGROUND: 1, 8-naphthimide is a novel tumor inhibitor targeting nuclear DNA, which can be used to design and develop anti-osteosarcoma drugs. OBJECTIVE: Quantitative structure-activity relationship (QSAR) model was established to predict the physical properties of compounds. METHODS: In this study, gene expression programming (GEP) was used to build a nonlinear quantitative structureactivity relationship (QSAR) model with descriptors and to predict the activity of a serials novel DNA-targeted chemotherapeutic agents. These descriptors were calculated in CODESSA software and selected from the descriptor pool based on heuristics. Three descriptors were selected to establish a multiple linear regression model. The best nonlinear QSAR model with a correlation coefficient of 0.89 and 0.82 and mean error of 0.02 and 0.06 for the training and test sets were obtained. RESULTS: The results showed that the model established by GEP had better stability and predictive ability. The small molecular docking experiment of 32 compounds was carried out in SYBYL software, and it was found that compound 7A had reliable molecular docking ability. CONCLUSION: The established model reveals the factors affecting the activity of DNA inhibitors and provides direction and guidance for the further design of highly effective DNA-targeting drugs for osteosarcoma.

Effective treatment in lung adenocarcinoma patient with brain metastases harboring novel CLHC1/RNT4 intergenic region- ALK fusion: A case report.

RATIONALE: Anaplastic lymphoma kinase (ALK) fusion, an important oncogenic mutation, occurs in 3% to 7% of non-small cell lung cancer (NSCLC) cases, and EML4 is the most common partner gene. With the widespread application of next-generation sequencing (NGS), more gene breakpoint fusions have been discovered and functional fusion transcripts can provide targeted clinical benefits. PATIENT CONCERNS AND DIAGNOSIS: A 40-year-old woman was diagnosed with lung adenocarcinoma with brain metastases. A novel CLHC1/RNT4 intergenic region, ALK (Exon20-29) (abundance 39.97%), was identified using lung puncture tissue by NGS analysis (Simceredx), and results of immunohistochemistry and fluorescence in situ hybridization confirmed ALK fusion. INTERVENTIONS AND OUTCOMES: The patient was administered oral crizotinib (250 mg bid) combined with endostar (30 mg d1-7) for 12 cycles from June 18, 2020. The patient's condition was controlled, and the curative effect was evaluated as stable disease (SD). Unfortunately, brain magnetic resonance images showed multiple nodules in the left cerebellar hemisphere, and chest computed tomography showed no significant changes in the progression of the disease. Subsequently, alectinib (600 mg bid) was administered on April 1, 2021. Brain lesions were significantly reduced and partial remission (PR) was achieved. No significant changes were observed in the lung lesions. LESSONS: ALK fusion is a risk factor for brain metastasis (BM) in patients with advanced non-small NSCLC patients. In our case, a novel CLHC1/RNT4 intergenic region, ALK fusion, was identified for the first time in a lung adenocarcinoma patient with BM, who benefited from crizotinib and endostar sequential alectinib. Our case highlights the advantages of NGS for fusion detection and provides promising treatment options for NSCLC patients with BM harboring ALK fusions.