The in silico identification of potent anti-cancer agents by targeting the ATP binding site of the N-domain of HSP90

Phase Ib study of HSP90 inhibitor, onalespib (AT13387), in combination with paclitaxel in patients with advanced triple-negative breast cancer

Background

Heat shock protein 90 (HSP90) is a molecular chaperone required for stabilization of client proteins over-activated in triple-negative breast cancer (TNBC). Over-expression of HSP90 client proteins has been implicated in paclitaxel resistance. Onalespib (AT13387) is a potent inhibitor of HSP90 that could improve paclitaxel efficacy when administered in combination.

Design

This phase Ib trial administered onalespib with paclitaxel in patients with advanced TNBC to assess safety and establish a recommended phase II dose (RP2D).

Objectives

The primary objectives were determining the dose-limiting toxicities and maximum tolerated dose of combination therapy. Secondary objectives included pharmacokinetic (PK) analysis and determination of overall response rate (ORR), duration of response (DOR), and progression-free survival (PFS).

Methods

Patients with advanced TNBC were treated with standard dose intravenous paclitaxel in combination with intravenous onalespib at doses ranging from 120 to 260 mg/m2 administered on days 1, 8, and 15 of a 28-day cycle using a standard 3 + 3 design. A total of 15 patients were enrolled to dose expansion cohort at RP2D to confirm safety profile.

Results

Thirty-one patients were enrolled in the study, of which over 90% had received prior taxane therapy. Paclitaxel was given for metastatic disease in 23% of patients. Adverse events (AEs) included anemia (grade 3: 20%), lymphopenia (grade 3: 17%), and neutropenia (grade 3: 33%, grade 4: 4%). The most frequent grade ⩾3 non-hematologic AE was diarrhea (7%). The established RP2D was 260 mg/m2 onalespib when given with paclitaxel at 80 mg/m2. PK analysis revealed a modest drug interaction profile for onalespib in the combination regimen. ORR was 20%. Three patients achieved complete responses, all of whom had received prior taxane therapy. Median DOR was 5.6 months; median PFS was 2.9 months.

Conclusion

Combination treatment with onalespib and paclitaxel had an acceptable toxicity profile and RP2D was determined to be 260 mg/m2 of onalespib. Combination therapy showed antitumor activity in patients with advanced TNBC.

Trial registration

Onalespib and paclitaxel in treating patients with advanced TNBC https://clinicaltrials.gov/ct2/show/NCT02474173.

Identifying SARS-CoV-2 main protease inhibitors by applying the computer screening of a large database of molecules

The outbreak of coronavirus disease 2019 (COVID-19) at the end of 2019 affected global health. Its infection agent was called severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Wearing a mask, maintaining social distance, and vaccination are effective ways to prevent infection of SARS-CoV-2, but none of them help infected people. Targeting the enzymes of SARS-CoV-2 is an effective way to stop the replication of the virus in infected people and treat COVID-19 patients. SARS-CoV-2 main protease is a therapeutic target which the inhibition of its enzymatic activity prevents from the replication of SARS-CoV-2. A large database of molecules has been searched to identify new inhibitors for SARS-CoV-2 main protease enzyme. At the first step, ligand screening based on similarity search was used to select similar compounds to known SARS-CoV-2 main protease inhibitors. Then molecules with better predicted pharmacokinetic properties were selected. Structure-based virtual screening based on the application of molecular docking and molecular dynamics simulation methods was used to select more effective inhibitors among selected molecules in previous step. Finally two compounds were considered as SARS-CoV-2 main protease inhibitors.

Computational study on subfamilies of piperidine derivatives: QSAR modelling, model external verification, the inter-subset similarity determination, and structure-based drug designing

A new subset of furan-pyrazole piperidine derivatives was used for QSAR model development. These compounds exhibit good Akt1 inhibitory activity; moreover, antiproliferative activities in vitro against OVCAR-8 (Human ovarian carcinoma cells) and HCT116 (human colon cancer cells), were confirmed for them. Based on the relevant three-dimensional (3D) and 2D autocorrelation descriptors, selected by genetic algorithm (GA), multiple linear regression (MLR) was established on half maximal-inhibitory concentration (IC₅₀), in Akt1 and cancer cell lines independently. Robustness, stability, and predictive ability of the models were evaluated using external and internal validation (r²: 0.742-0.832, Q²_LOO: 0.684-0.796, RMSE: 0.247-0.299, F: 32.283-57.578, and r²_y-random: 0.049-0.080). Furthermore, in the new strategy, each of the evaluated models was generalized to two other subfamilies of piperidines to simultaneously compare the activities and structural similarity of these three subsets. Probably, structural similarity can be more considered as a criterion of similarity in the mechanism of action. Also, external verification of suggested predictive models was performed by another subset. Finally, by focusing on M64 as the most potent in vivo antitumor compound, 15 new derivatives were designed and six potent candidates were proposed for further investigation.

Understanding the Hsp90 N-terminal Dynamics: Structural and Molecular Insights into the Therapeutic Activities of Anticancer Inhibitors Radicicol (RD) and Radicicol Derivative (NVP-YUA922)

Heat shock protein 90 (Hsp90) is a crucial component in carcinogenesis and serves as a molecular chaperone that facilitates protein maturation whilst protecting cells against temperature-induced stress. The function of Hsp90 is highly dependent on adenosine triphosphate (ATP) binding to the N-terminal domain of the protein. Thus, inhibition through displacement of ATP by means of competitive binding with a suitable organic molecule is considered an attractive topic in cancer research. Radicicol (RD) and its derivative, resorcinylic isoxazole amine NVP-AUY922 (NVP), have shown promising pharmacodynamics against Hsp90 activity. To date, the underlying binding mechanism of RD and NVP has not yet been investigated. In this study, we provide a comprehensive understanding of the binding mechanism of RD and NVP, from an atomistic perspective. Density functional theory (DFT) calculations enabled the analyses of the compounds' electronic properties and results obtained proved to be significant in which NVP was predicted to be more favorable with solvation free energy value of -23.3 kcal/mol and highest stability energy of 75.5 kcal/mol for a major atomic delocalization. Molecular dynamic (MD) analysis revealed NVP bound to Hsp90 (NT-NVP) is more stable in comparison to RD (NT-RD). The Hsp90 protein exhibited a greater binding affinity for NT-NVP (-49.4 ± 3.9 kcal/mol) relative to NT-RD (-28.9 ± 4.5 kcal/mol). The key residues influential in this interaction are Gly 97, Asp 93 and Thr 184. These findings provide valuable insights into the Hsp90 dynamics and will serve as a guide for the design of potent novel inhibitors for cancer treatment.

Development linear and non-linear QSAR models for predicting AXL kinase inhibitory activity of N-[4-(quinolin-4-yloxy)phenyl]benzenesulfonamides

In this research, we used CoMFA, LSSVM and FFANN for creating QSAR models for predicting AXL Kinase inhibitory activity of N-[4-(Quinolin-4-yloxy)phenyl]benzenesulfonamides. A CoMFA model with three components was developed and CoMFA contour maps were interpreted to extract chemical features that influence the inhibitory activity of these molecules. R2 for train and test set of CoMFA model were 0.8900 and 0.8171, respectively. Model created by five Dragon descriptors and LSSVM model showed slightly better predictive power with respect to CoMFA model. R2 for train, test set of created LSSVM model were 0.0.8477 and 0.8218, respectively. Also, a FFANN model, using the same five descriptors, was developed with 2 neurons in its hidden layer and R2 for its train and test sets were 0.8314 and 0.8522, respectively. All created models were validated by calculating several statistical parameters and their applicability domain were investigated by calculating leverage. Furthermore, a homology model was built for Axl structure and molecules with the lowest and the greatest activity were docked to it and their interactions with Axl were investigated.

Design of new CD38 inhibitors based on CoMFA modelling and molecular docking analysis of 4‑amino-8-quinoline carboxamides and 2,4-diamino-8-quinazoline carboxamides

In this study, based on molecular docking analysis and comparative molecular field analysis (CoMFA) modelling of a series of 71 CD38 inhibitors including 4‑amino-8-quinoline carboxamides and 2,4-diamino-8-quinazoline carboxamides, new CD38 inhibitors were designed. The interactions of the molecules with the greatest and the lowest activities with the nicotinamide mononucleotide (NMN) binding site were investigated by molecular docking analysis. A CoMFA model with four partial least squares regression (PLSR) components was developed to predict the CD38 inhibitory activity of the molecules. The r² values for the training and test sets were 0.89 and 0.82, respectively. The Q² values for leave-one-out cross-validation (LOO-CV) and leave-many-out cross-validation (LMO-CV) tests on the training set were 0.65 and 0.64, respectively. The CoMFA model was validated by calculating several statistical parameters. CoMFA contour maps were interpreted, and structural features that influence the CD38 inhibitory activity of molecules were determined. Finally, seven new CD38 inhibitors with greater activity with respect to the greatest active molecules were designed.