Proto-Oncogene Proteins B-raf

Two experiments were applied for each target:(a)

Self-docking of each ligand inside its own protein structural conformation.

(b)

Cross-docking of three selected ligands inside the remaining nine protein structures.

All the studied ligands in this work were prepared using LigPrep with the force field OPLS_2005 [61 (link)]. Docking tests were performed using the softwares Glide and Autodock. Glide offers a complete solution for ligand–receptor docking and is widely used for drug discovery [62 (link),63 (link)], virtual screening [64 (link),65 (link)], structure-activity relationship analysis [9 (link),66 (link)], etc. Grid boxes for self-docking and cross-docking experiments were centered in the ligand position coming from the crystal structures. The grid boxes’ dimensions were (20 × 20 × 20) ų in order to include the whole binding site for the three targets under study. High-throughput virtual screening (HTVS), standard precision (SP), and extra precision (XP) Glide modes were proved. Default docking parameters were used. Glide docking uses hierarchical filters to find the best ligand binding locations in the defined receptor grid space. The filters include positional, conformational, and orientational sampling of the ligand and subsequent energy evaluation of the interactions between the ligand and the protein [18 (link),19 (link),20 (link)]. Ligand minimization in the receptor field is carried out using the OPLS-AA force field [67 (link)] with a distance-dependent dielectric of 2.0. Afterward, the lowest energy poses are subjected to a Monte Carlo (MC) procedure that samples the nearby torsional minima. The best poses for a given ligand are determined by the GlideScore score [68 (link)], including terms for buried polar groups and steric clashes.
Autodock parameters were defined in a similar way as in Glide, with grid boxes dimensions of 20 × 20 × 20 ų. AutoDock uses a semi-empirical free energy force field to predict binding energies or ligands to macromolecular targets and Lamarckian genetic algorithm (GA) to search for docking solutions [69 (link)]. The force field is based on a comprehensive thermodynamic model that allows incorporation of intramolecular energies into the predicted free energy of binding [70 (link)]. Each ligand was located in the grid box for each docking run and torsional degrees of freedom were defined. The GA was applied with an initial population of 100 randomly placed individuals, a maximum number of 1 × 10⁶ energy evaluations, a maximum number of 3 × 10⁴ generations, a mutation rate of 0.02, a crossover rate of 0.80, and an elitism value of 2.
Each self-docking or cross-docking experiment between a target protein (MAO-B, thrombin or B-RAF) and a ligand was repeated three times, accounting for replicated instances. The effectiveness of the docking experiment (self-docking or cross-docking) in reproducing the crystallographic binding orientation of a ligand $\mathit{\alpha }$ was determined by comparing the docked pose with the orientation of the ligand in its native crystallographic structure ${\mathit{A}}_{\mathit{\alpha }}$ . In the case of MAO-B, the cofactor FAD was present in the binding site during docking experiments. The RMSD was employed as the term for performing such comparison, where ligand atoms were matched one to one and symmetrical atoms were considered equivalent. For comparing cross-docking poses, receptor structures were superimposed using Cα of binding site amino acids, by considering that amino acids that surround 10 Å the ligand in its native crystallographic structure form the binding site.

Patient-derived organoid generation was attempted from baseline biopsies of all patients. A total of 10 colorectal tumor organoid lines were successfully generated from tumor baseline biopsies of 10 patients enrolled in the BRAF/MEK/PD-1 inhibition trial (patients 1, 2, 4, 10, 11, 14, 16, 18, 21 and 24). Tumor biopsies were transported in ice-cold RPMI with 10% human serum and transferred into a petri dish on ice before processing. Tumor biopsies were minced and subjected to enzymatic dissociation in 4.75 ml minimum essential medium for suspension cultures (Gibco) supplemented with 250 µl Liberase for 45 min at 37 °C using a heater-shaker. Following the dissociation, tumor biopsies were centrifuged at 300g for 5 min, seeded into Matrigel in a prewarmed 24-well plate and cultured with 500 µl of basal growth media. For passaging, organoids were mechanically pipetted out of Matrigel using Corning Cell Recovery Solution (Corning), followed by a 1-h incubation at 4 °C. Organoid fragments were then centrifuged and subjected to enzymatic dissociation in Tryple E (Gibco) for 5 min at 37 °C. A 20-gauge needle was used to further disrupt the organoids mechanically. DMEM/F12 media supplemented with 10% FBS was added to the conical tube to stop the enzymatic reaction. Dissociated organoids were collected by centrifugation and seeded in Matrigel as above; 10 µM Rko-Kinase inhibitor was added to the basal growth media for organoid passaging. For drug treatment, dissociated organoids were resuspended in basal growth media supplemented with 2% Matrigel and plated in a 24-well plate coated with 250 µl Matrigel. The next day, organoids were treated with dabrafenib (100 nM) + trametinib (10 nM), dabrafenib (100 nM) + ERAS007 (100 nM), or dabrafenib (100 nM) + panitumumab (3 µg ml⁻¹; McKesson) for 72 h. The drugs were refreshed every 24 h. After the treatment, organoids were collected and subjected to RNA extraction. For cell viability experiments, dissociated organoids supplemented with 2% Matrigel were plated in a 96-well plate coated with 70 µl Matrigel; 48 h later, organoids were treated with various doses of dabrafenib + trametinib or dabrafenib + ERAS007 for 72 h and subjected to cell viability measurement using CellTiter-Glo 3D (Promega).

Data collected included sex, age, surgical method, thyroid peroxidase antibody (TPOAb), thyroglobulin antibody (TGAb), thyroid hormone receptor antibody (TRAb), microcalcification foci, positive lymph node number, BRAF gene mutation(V600E), TERT promoter mutation(C228, C250), RET/PTC chromosomal rearrangement(RET/PTC1, RET/PTC3), HRAS gene mutation(Q61), KRAS gene mutation(G12, G13), and NRAS gene mutation(Q61). All data from preoperative examinations and postoperative pathological reports, such as cervical ultrasonic and CT, laboratory examination, and gene test results, were evaluated.
All preoperative examinations were confirmed by a radiologist and chief surgeon, who confirmed the number, size, and calcification of carcinoma and evaluated the lymph node state. Metastatic lymph nodes were suspected when lymph nodes showed increased size (>0.5 cm), demarcation of the cortex and medulla was unclear or the structure of the medulla disappeared, gravel-like calcification or cystic degeneration, rounded bulging shape, and abnormal blood flow or vascularity. Hashimoto’s thyroiditis (HT) was diagnosed when the thyroid gland was diffusely enlarged with hypoechogenicity, and the gland parenchyma was inhomogeneous with grid-like or compartment-like changes or appeared abnormal TPOAb, TGAb, TRAb results (8 (link), 9 (link)). A gene mutation detection kit (Shanghai Anjia Biological Technology Co., Ltd.) was used to detect BRAF, TERT, HRAS, KRAS, NRAS mutations and RET/PTC rearrangements according to the manufacturer’s instructions. The scope of CLND was superior to the hyoid bone, lateral to the carotid sheath, inferior to the sternum notch or the innominate artery, medial to the trachea and dorsal to the prevertebral fascia.