Elucidation of binding mode and three dimensional quantitative structure-activity relationship studies of a novel series of protein kinase B/Akt inhibitors

Combined 3D-QSAR, molecular docking and dynamics simulations studies to model and design TTK inhibitors

Tyrosine threonine kinase (TTK) is the key component of the spindle assembly checkpoint (SAC) that ensures correct attachment of chromosomes to the mitotic spindle and thereby their precise segregation into daughter cells by phosphorylating specific substrate proteins. The overexpression of TTK has been associated with various human malignancies, including breast, colorectal and thyroid carcinomas. TTK has been validated as a target for drug development, and several TTK inhibitors have been discovered. In this study, ligand and structure-based alignment as well as various partial charge models were used to perform 3D-QSAR modelling on 1H-Pyrrolo[3,2-c] pyridine core containing reported inhibitors of TTK protein using the comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) approaches to design better active compounds. Different statistical methods i.e., correlation coefficient of non-cross validation (r2), correlation coefficient of leave-one-out cross-validation (q2), Fisher's test (F) and bootstrapping were used to validate the developed models. Out of several charge models and alignment-based approaches, Merck Molecular Force Field (MMFF94) charges using structure-based alignment yielded highly predictive CoMFA (q2 = 0.583, Predr2 = 0.751) and CoMSIA (q2 = 0.690, Predr2 = 0.767) models. The models exhibited that electrostatic, steric, HBA, HBD, and hydrophobic fields play a key role in structure activity relationship of these compounds. Using the contour maps information of the best predictive model, new compounds were designed and docked at the TTK active site to predict their plausible binding modes. The structural stability of the TTK complexes with new compounds was confirmed using MD simulations. The simulation studies revealed that all compounds formed stable complexes. Similarly, MM/PBSA method based free energy calculations showed that these compounds bind with reasonably good affinity to the TTK protein. Overall molecular modelling results suggest that newly designed compounds can act as lead compounds for the optimization of TTK inhibitors.

AKT Inhibitors: The Road Ahead to Computational Modeling-Guided Discovery

AKT, is a serine/threonine protein kinase comprising three isoforms-namely: AKT1, AKT2 and AKT3, whose inhibitors have been recognized as promising therapeutic targets for various human disorders, especially cancer. In this work, we report a systematic evaluation of multi-target Quantitative Structure-Activity Relationship (mt-QSAR) models to probe AKT' inhibitory activity, based on different feature selection algorithms and machine learning tools. The best predictive linear and non-linear mt-QSAR models were found by the genetic algorithm-based linear discriminant analysis (GA-LDA) and gradient boosting (Xgboost) techniques, respectively, using a dataset containing 5523 inhibitors of the AKT isoforms assayed under various experimental conditions. The linear model highlighted the key structural attributes responsible for higher inhibitory activity whereas the non-linear model displayed an overall accuracy higher than 90%. Both these predictive models, generated through internal and external validation methods, were then used for screening the Asinex kinase inhibitor library to identify the most potential virtual hits as pan-AKT inhibitors. The virtual hits identified were then filtered by stepwise analyses based on reverse pharmacophore-mapping based prediction. Finally, results of molecular dynamics simulations were used to estimate the theoretical binding affinity of the selected virtual hits towards the three isoforms of enzyme AKT. Our computational findings thus provide important guidelines to facilitate the discovery of novel AKT inhibitors.

Investigations of Structural Requirements for BRD4 Inhibitors through Ligand- and Structure-Based 3D QSAR Approaches

The bromodomain containing protein 4 (BRD4) recognizes acetylated histone proteins and plays numerous roles in the progression of a wide range of cancers, due to which it is under intense investigation as a novel anti-cancer drug target. In the present study, we performed three-dimensional quantitative structure activity relationship (3D-QSAR) molecular modeling on a series of 60 inhibitors of BRD4 protein using ligand- and structure-based alignment and different partial charges assignment methods by employing comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) approaches. The developed models were validated using various statistical methods, including non-cross validated correlation coefficient (r²), leave-one-out (LOO) cross validated correlation coefficient (q²), bootstrapping, and Fisher’s randomization test. The highly reliable and predictive CoMFA (q² = 0.569, r² = 0.979) and CoMSIA (q² = 0.500, r² = 0.982) models were obtained from a structure-based 3D-QSAR approach using Merck molecular force field (MMFF94). The best models demonstrate that electrostatic and steric fields play an important role in the biological activities of these compounds. Hence, based on the contour maps information, new compounds were designed, and their binding modes were elucidated in BRD4 protein’s active site. Further, the activities and physicochemical properties of the designed molecules were also predicted using the best 3D-QSAR models. We believe that predicted models will help us to understand the structural requirements of BRD4 protein inhibitors that belong to quinolinone and quinazolinone classes for the designing of better active compounds.

A 2D-QSAR and Grid-Independent Molecular Descriptor (GRIND) Analysis of Quinoline-Type Inhibitors of Akt2: Exploration of the Binding Mode in the Pleckstrin Homology (PH) Domain

Protein kinase B-β (PKBβ/Akt2) is a serine/threonine-specific protein kinase that has emerged as one of the most important regulators of cell growth, differentiation, and division. Upregulation of Akt2 in various human carcinomas, including ovarian, breast, and pancreatic, is a well-known tumorigenesis phenomenon. Early on, the concept of the simultaneous administration of anticancer drugs with inhibitors of Akt2 was advocated to overcome cell proliferation in the chemotherapeutic treatment of cancer. However, clinical studies have not lived up to the high expectations, and several phase II and phase III clinical studies have been terminated prematurely because of severe side effects related to the non-selective isomeric inhibition of Akt2. The notion that the sequence identity of pleckstrin homology (PH) domains within Akt-isoforms is less than 30% might indicate the possibility of the development of selective antagonists against the Akt2 PH domain. Therefore, in this study, various in silico tools were utilized to explore the hypothesis that quinoline-type inhibitors bind in the Akt2 PH domain. A Grid-Independent Molecular Descriptor (GRIND) analysis indicated that two hydrogen bond acceptors, two hydrogen bond donors and one hydrophobic feature at a certain distance from each other were important for the selective inhibition of Akt2. Our docking results delineated the importance of Lys30 as an anchor point for mapping the distances of important amino acid residues in the binding pocket, including Lys14, Glu17, Arg25, Asn53, Asn54 and Arg86. The binding regions identified complement the GRIND-based pharmacophoric features.

Efficacy of nimotuzumab combined with docetaxel-cisplatin-fluorouracil regimen in treatment of advanced oral carcinoma

The present study aimed to evaluate efficacy and adverse effects of Nimotuzumab combined with docetaxel-cisplatin-fluorouracil regimen in the treatment of advanced oral carcinoma. Nine patients with advanced oral carcinoma were treated with Nimotuzumab combined with docetaxel-cisplatin-fluorouracil regimen (test group). The treatment was given as follows: Nimotuzumab 200 mg, given as intravenous infusion once a week for 6 weeks; docetaxel and cisplatin, 75 mg/m(2) each, on day 1 only; 5-fluorouracil, 750 mg/m(2) infused continually for 8 h, used from day 1 to 5; the total cycle was for 21 days. Another eight patients comprised control group (docetaxel-cisplatin-fluorouracil regimen alone). Study patients from both groups were evaluated for objective response. The response rate was significantly (p = 0.044) higher in test group (88.9 vs. 37.5 % in control group). The disease control rate also tended to be higher in test group (100 vs. 62.5 % in control group; p = 0.083). The major adverse effects were bone marrow suppression, nausea, vomiting, and alopecia. The incidence of adverse effects was similar between both study groups. In conclusion, Nimotuzumab combined with docetaxel-cisplatin-fluorouracil regimen is effective and safe in the treatment of advanced oral carcinoma.

Anti-HER-2 anti-CD3 bi-specific antibodies inhibit growth of HCT-116 colorectal carcinoma cells in vitro and in vivo

OBJECTIVE

This study is conducted to evaluate the effects of anti-HER-2 anti-CD3 bi-specific antibodies(BsAb) on HER-2/neuover-expressing human colorectal carcinoma cells.

METHODS

Growth was assessed by MTT assays after exposure of HCT-116 cells to Herceptin, anti-CD3 and BsAb antibodies. Immunocytochemistry was applied to test the HER-2 level of HCT-116. In a nude mouse model, HER-2 CD3 BsAb was combined with effector cells (peripheral blood lymph cells from normal human being) for observations on in Vivo growth of tumors.

RESULTS

Compared with the control group, using effector cells combined with anti-CD3 McAb, Herceptin or HER2 CD3 BsAb, tumor cell growth in vitro and in vivo was significantly inhibited (P<0.05), most remarkably in the HER2 CD3 BsAb case. The growth of xenografts with HER2 CD3 BsAb combined with effector cells was also significantly inhibited when compared with the anti-CD3 McAb or Herceptin groups (P<0.05).

CONCLUSION

HER-2/neu might be a useful target for immunotherapy in colorectal carcinoma, anti-HER2 anti-CD3 BsAb exerting clear anti-tumor effects.

Charge heterogeneity of a therapeutic monoclonal antibody conjugated with a cytotoxic antitumor antibiotic, calicheamicin

A robust and highly reproducible capillary isoelectric focusing (cIEF) method for the evaluation of charge heterogeneity of monoclonal antibody (mAb) pharmaceutical which contains covalently bound antitumor compounds was developed using a combination of commercially available dimethylpolysiloxane-coated capillary and carrier ampholyte. In order to optimize major analytical parameters for robust mobilization, experimental responses from three pI markers were selected. The optimized method gave excellent repeatability and intermediate precision in estimated pI values of charge variants with relative standard deviations (RSDs) of not more than 0.06% and 0.95%, respectively, when using IgG(4) as a model. Furthermore, RSDs of charge variant compositions were less than 5.0%. These results suggest that the proposed method can be a powerful tool for reproducible evaluation of charge variants of both naked mAbs and their conjugates with high resolution, and it is applicable to quality testing and detailed characterization in the pharmaceutical industry. In addition, it should be noticed that the method provided non-linear pH gradient within the tested ranges, from pI 9.50 to 3.78, and the pH gradient caused the inconsistency of estimated pI ranges between cIEF and gel IEF. This result indicates that selecting appropriate pI markers based on the target pI ranges of charge variants for each mAb related pharmaceutical is highly recommended for the precise determination of pI values.

A comprehensive structure-activity analysis of protein kinase B-alpha (Akt1) inhibitors

Protein kinase B (PKB, also known as Akt) belongs to the AGC subfamily of the protein kinase superfamily. Akt1 has been reported as a central player in regulation of metabolism, cell survival, motility, transcription and cell-cycle progression, among the signalling proteins that respond to a large variety of signals. In this study an attempt was made to understand structural requirements for Akt1 inhibition using conventional QSAR, k-nearest neighbour QSAR and novel GQSAR methods. With this intention, a wide variety of structurally diverse Akt1 inhibitors were collected from various literature reports. The conventional QSAR analyses revealed the key role of Baumann's alignment independent topological descriptors along with other descriptors such as the number of hydrogen bond acceptors, hydrogen bond donors, rotatable bonds and aromatic oxygen (SaaOcount) along with molecular branching (chi3Cluster), alkene carbon atom type (SdsCHE-index) in governing activity variation. Further, the GQSAR analyses show that chemical variations like presence of hetero-aromatic ring, flexibility, polar surface area and fragment length present in the hinge binding fragment (in the present case fragment D) are highly influential for achieving highly potent Akt1 inhibitors. In addition, this study resulted in a k-nearest neighbour classification model with three descriptors suggesting the key role of oxygen (SssOE-index) and aromatic carbon (SaaCHE-index and SaasCE-index) atoms electro-topological environment that differentiate molecules binding to Akt1 kinase or PH domain. The developed models are interpretable, with good statistical and predictive significance, and can be used for guiding ligand modification for the development of potential new Akt1 inhibitors.