Conformational States of E7010 Is Complemented by Microclusters of Water Inside the α,β-Tubulin Core

Molecular Dynamics and Machine Learning reveal distinguishing mechanisms of Competitive Ligands to perturb α,β-Tubulin

The mechanisms of action of ligands competing for the Colchicine Binding Site (CBS) of the α,β-Tubulin are non-standard compared to the commonly witnessed ligand-induced inhibition of proteins. This is because their potencies are not solely judged by the binding affinity itself, but also by their capacity to bias the conformational states of the dimer. Regarding the latter requirement, it is observed that ligands competing for the same pocket that binds colchicine exhibit divergence in potential clinical outcomes. Molecular dynamics-based ∼5.2 µs sampling of α,β-Tubulin complexed with four different ligands has revealed that each ligand has its customized way of influencing the complex. Primarily, it is the proportion of twisting and/or bending characteristic of modes of the intrinsic dynamics which is revealed to be 'fundamental' to tune this variation in the mechanism. The milder influence of 'bending' makes a ligand (TUB092), better classifiable under the group of vascular disrupting agents (VDAs), which are phenotypically effective on cytoskeletons; whereas a stronger impact of 'bending' makes the classical ligand Colchicine (COL) a better Anti-Mitotic agent (AMA). Two other ligands BAL27862 (2RR) and Nocodazole (NZO) fall in the intermediate zone as they fail to explicitly induce bending modes. Random Forest Classification method and K-means Clustering is applied to reveal the efficiency of Machine Learning methods in classifying the Tubulin conformations according to their ligand-specific perturbations and to highlight the significance of specific amino acid residues, mostly positioned in the α-β and β-β interfaces involved in the mechanism. These key residues responsible to yield discriminative actions of the ligands are likely to be highly useful in future endeavours to design more precise inhibitors.

DOX_BDW: Incorporating Solvation and Desolvation Effects of Cavity Water into Nonfitting Protein-Ligand Binding Affinity Prediction

Accurate prediction of the protein-ligand binding affinity (PLBA) with an affordable cost is one of the ultimate goals in the field of structure-based drug design (SBDD), as well as a great challenge in the computational and theoretical chemistry. Herein, we have systematically addressed the complicated solvation and desolvation effects on the PLBA brought by the difference of the explicit water in the protein cavity before and after ligands bind to the protein-binding site. Based on the new solvation model, a nonfitting method at the first-principles level for the PLBA prediction was developed by taking the bridging and displaced water (BDW) molecules into account simultaneously. The newly developed method, DOX_BDW, was validated against a total of 765 noncovalent and covalent protein-ligand binding pairs, including the CASF2016 core set, Cov_2022 covalent binding testing set, and six testing sets for the hit and lead compound optimization (HLO) simulation. In all of the testing sets, the DOX_BDW method was able to produce PLBA predictions that were strongly correlated with the corresponding experimental data (R = 0.66-0.85). The overall performance of DOX_BDW is better than the current empirical scoring functions that are heavily parameterized. DOX_BDW is particularly outstanding for the covalent binding situation, implying the need for considering an electronic structure in covalent drug design. Furthermore, the method is especially recommended to be used in the HLO scenario of SBDD, where hundreds of similar derivatives need to be screened and refined. The computational cost of DOX_BDW is affordable, and its accuracy is remarkable.

Computational Approaches to the Rational Design of Tubulin-Targeting Agents

Microtubules are highly dynamic polymers of α,β-tubulin dimers which play an essential role in numerous cellular processes such as cell proliferation and intracellular transport, making them an attractive target for cancer and neurodegeneration research. To date, a large number of known tubulin binders were derived from natural products, while only one was developed by rational structure-based drug design. Several of these tubulin binders show promising in vitro profiles while presenting unacceptable off-target effects when tested in patients. Therefore, there is a continuing demand for the discovery of safer and more efficient tubulin-targeting agents. Since tubulin structural data is readily available, the employment of computer-aided design techniques can be a key element to focus on the relevant chemical space and guide the design process. Due to the high diversity and quantity of structural data available, we compiled here a guide to the accessible tubulin-ligand structures. Furthermore, we review different ligand and structure-based methods recently used for the successful selection and design of new tubulin-targeting agents.

Mechanisms of influence of the microtubule over-stabilizing ligands on the structure and intrinsic dynamics of α,β-Tubulin

The intervention into the cell cycle progression by administering microtubule over-stabilizing ligands that arrest the mitotic cell division by preventing spindle dissociation, is a promising strategy to fight against cancers. The building blocks of the microtubules and the spindles, i.e. the α,β-tubulin dimer, upon binding of such ligands, stay more comfortably in the microtubular multimeric form; the phenomenon of which is the key to the said over-stabilization. Using two such over-stabilizing ligands, Taxol and Taxotere, the present work reports the collective changes that these ligands induce on the structure and dynamics of the α,β-tubulin dimer which could be reconciled as the molecular basis of the over-stabilization of the microtubules; the trends have been found to be statistically significant across all independent calculations on them. The ligand binding increases the coherence between the residue communities of the two opposite faces of the β-subunit, which in a periodic arrangement in microtubule are knwon to form intermolecular contact with each other. This is likely to create an indirect cooperativity between those structural regions and this is a consequence of the reshuffling of the internal network of interactions upon ligand binding. Such reorganizations are also complemented by the increased contributions of the softer modes of the intrinsic dynamics more, which is likely to increase the plasticity of the system favourable for making structural adjustments in a multimer. Further, the ligands are able to compensate the drawback of lacking one phosphate group in protein-GDP interactions compared to the same for protein-GTP and this is in agreement with the hints form the earlier reports. The findings form a mechanistic basis of the enhanced capacity of the α,β-tubulin dimer to get more favourably accommodated into the microtubule superstructure upon binding either of Taxol and Taxotere.

Design, Synthesis and Evaluation of 2,4-Diaminoquinazoline Derivatives as Potential Tubulin Polymerization Inhibitors

Microtubules are highly dynamic polymers composed of α- and β-tubulin proteins that have been shown to be potential therapeutic targets for the development of anticancer drugs. Currently, a wide variety of chemically diverse agents that bind to β-tubulin have been reported. Nocodazole (NZ) and colchicine (COL) are well-known tubulin-depolymerizing agents that have close binding sites in the β-tubulin. In this study, we designed and synthesized a set of nine 2,4-diaminoquinazoline derivatives that could occupy both NZ and COL binding sites. The synthesized compounds were evaluated for their antiproliferative activities against five cancer cell lines (PC-3, HCT-15, MCF-7, MDA-MB-231, and SK-LU-1), a noncancerous one (COS-7), and peripheral blood mononuclear cells (PBMC). The effect of compounds 4 e and 4 i on tubulin organization and polymerization was analyzed on the SK-LU-1 cell line by indirect immunofluorescence, western blotting, and tubulin polymerization assays. Our results demonstrated that both compounds exert their antiproliferative activity by inhibiting tubulin polymerization. Finally, a possible binding pose of 4 i in the NZ/COL binding site was determined by using molecular docking and molecular dynamics (MD) approaches. To our knowledge, this is the first report of non-N-substituted 2,4-diaminoquinazoline derivatives with the ability to inhibit tubulin polymerization.

Discovery, biological evaluation, structure-activity relationships and mechanism of action of pyrazolo[3,4-b]pyridin-6-one derivatives as a new class of anticancer agents

We have recently reported computational models for prediction of cell-based anticancer activity using machine learning methods. Herein, we have developed an integrated strategy to discover new anticancer agents using a cascade of the established screening models. Application of this strategy identified 17 compounds with antitumor activity. Among these compounds, h2 (containing a pyrazolo[3,4-b]pyridin-6-one scaffold) exhibited anticancer activity against six tumor cell lines, including MDA-MB-231, HeLa, MCF-7, HepG2, CNE2 and HCT116, with IC50 values of 13.37, 13.04, 15.45, 7.05, 9.30 and 8.93 μM. Subsequently, a total of 61 h2 analogues were obtained by similarity searching and tested for their anticancer activities. I2 was identified as a novel anticancer agent having activity against MDA-MB-231, HeLa, MCF-7, HepG2, CNE2 and HCT116 tumor cell lines with IC50 values of 3.30, 5.04, 5.08, 3.71, 2.99 and 5.72 μM. I2 also showed potent cytotoxicity against adriamycin-resistant human breast and hepatocarcinoma cells. Further investigation revealed that I2 inhibited the microtubule polymerization by binding to the colchicine site, resulting in inhibition of cell migration, cell cycle arrest in the G2/M phase and apoptosis of cancer cells. Finally, molecular docking and molecular dynamics provided insights into the binding interactions of I2 with tubulin. This study identified I2 as a novel starting point for further development of anticancer agents that target tubulin.

A collective motion description of tubulin βT7 loop dynamics

Tubulin is a hetero-dimeric protein that polymerizes into microtubules and facilitates, among other things, eukaryotic cell division. Thus, any agent that interferes with tubulin polymerization is of therapeutic interest, vis-à-vis cancer. For example, colchicine is known to prevent tubulin polymerization by binding at the heterodimeric interface of αβ-tubulin. Crystal structures of tubulin bound to colchicine have shown that the dynamical conformation of a loop (βT7) plays an important role in colchicine binding. The βT7 loop dynamics also plays an important role in yielding curved versus straight αβ-tubulin dimers, only the latter being compatible with the microtubule assembly. Understanding the molecular mechanism of inhibition of microtubule assembly can lead to development of better therapeutic agents. In this work we were able to capture the βT7 loop flip by performing 200 ns molecular dynamics simulation of ligand-free αβ-tubulins. The loop flip could be described by only two independent collective vectors, obtained from principal component analysis. The first vector describes the flip while the second vector describes the trigger. The collective variables identified in this work is a natural reaction coordinate for functionally important tubulin dynamics, which allowed us to describe in detail the interaction network associated with the flip and the overall straight/curved conformational equilibrium.