Thiol versus hydroxamate as zinc binding group in HDAC inhibition: An ab initio QM/MM molecular dynamics study

DP/MM: A Hybrid Model for Zinc-Protein Interactions in Molecular Dynamics

Zinc-containing proteins are vital for many biological processes, yet accurately modeling them using classical force fields is hindered by complicated polarization and charge transfer effects. This study introduces DP/MM, a hybrid force field scheme that utilizes a deep potential model to correct the atomic forces of zinc ions and their coordinated atoms, elevating them from MM to QM levels of accuracy. Trained on the difference between MM and QM atomic forces across diverse zinc coordination groups, the DP/MM model faithfully reproduces structural characteristics of zinc coordination during simulations, such as the tetrahedral coordination of Cys4 and Cys3His1 groups. Furthermore, DP/MM allows water exchange in the zinc coordination environment. With its unique blend of accuracy, efficiency, flexibility, and transferability, DP/MM serves as a valuable tool for studying structures and dynamics of zinc-containing proteins and also represents a pioneering approach in the evolving landscape of machine learning potentials for molecular modeling.

The Impact of Fluorination on the Design of Histone Deacetylase Inhibitors

In recent years, histone deacetylases (HDACs) have emerged as promising targets in the treatment of cancer. The approach is to inhibit HDACs with drugs known as HDAC inhibitors (HDACis). Such HDACis are broadly classified according to their chemical structure, e.g., hydroxamic acids, benzamides, thiols, short-chain fatty acids, and cyclic peptides. Fluorination plays an important role in the medicinal-chemical design of new active representatives. As a result of the introduction of fluorine into the chemical structure, parameters such as potency or selectivity towards isoforms of HDACs can be increased. However, the impact of fluorination cannot always be clearly deduced. Nevertheless, a change in lipophilicity and, hence, solubility, as well as permeability, can influence the potency. The selectivity towards certain HDACs isoforms can be explained by special interactions of fluorinated compounds with the structure of the slightly different enzymes. Another aspect is that for a more detailed investigation of newly synthesized fluorine-containing active compounds, fluorination is often used for the purpose of labeling. Aside from the isotope ¹⁹F, which can be detected by nuclear magnetic resonance spectroscopy, the positron emission tomography of ¹⁸F plays a major role. However, to our best knowledge, a survey of the general effects of fluorination on HDACis development is lacking in the literature to date. Therefore, the aim of this review is to highlight the introduction of fluorine in the course of chemical synthesis and the impact on biological activity, using selected examples of recently developed fluorinated HDACis.

Phosphorus containing analogues of SAHA as inhibitors of HDACs

Histone deacetylases (HDACs) are a family of enzymes responsible for regulating DNA transcription by modulating its binding to histone proteins. HDACs are overexpressed in several types of cancers and are recognised as drug targets. Vorinostat, or suberanilohydroxamic acid (SAHA), is an histone deacetylase (HDAC) inhibitor with a hydroxamic acid as a zinc-binding group (ZBG), and it has been FDA approved for the treatment of T-cell lymphoma. In this work, phosphorus-based SAHA analogues were synthesised to assess their zinc-binding effectiveness compared to the hydroxamic acid of SAHA. Specifically, we examined phosphate, phosphoramidate and phosphorothiolate groups as isosteres of the canonical hydroxamic acid motif of conventional HDAC inhibitors. The compounds were screened for binding to HDAC enzymes from HeLa cell lysate. The most potent derivatives were then screened against HDAC3 and HDAC8 isoforms. HDAC inhibition assays demonstrated that these phosphorus-based SAHA analogs exhibited slow binding to HDACs but with greater potency than phosphonate SAHA analogs examined previously. All compounds inhibited HDACs, the most potent having an IC50 of 50 µM.

Transition metals and metal complexes in autophagy and diseases

Transition metals refer to the elements in the d and ds blocks of the periodic table. Since the success of cisplatin and auranofin, transition metal-based compounds have become a prospective source for drug development, particularly in cancer treatment. In recent years, extensive studies have shown that numerous transition metal-based compounds could modulate autophagy, promising a new therapeutic strategy for metal-related diseases and the design of metal-based agents. Copper, zinc, and manganese, which are common components in physiological pathways, play important roles in the progression of cancer, neurodegenerative diseases, and cardiovascular diseases. Furthermore, enrichment of copper, zinc, or manganese can regulate autophagy. Thus, we summarized the current advances in elucidating the mechanisms of some metals/metal-based compounds and their functions in autophagy regulation, which is conducive to explore the intricate roles of autophagy and exploit novel therapeutic drugs for human diseases.

An in silico mechanistic insight into HDAC8 activation facilitates the discovery of new small-molecule activators

Research interest in the development of histone deacetylase 8 (HDAC8) activators has substantially increased since loss-of-function HDAC8 mutations were found in patients with Cornelia de Lange syndrome (CdLS). A series of N-acetylthioureas (e.g., TM-2-51) have been identified as HDAC8-selective activators, among others; however, their activation mechanisms remain elusive. Herein, we performed molecular dynamics (MD) simulations and fragment-centric topographical mapping (FCTM) to investigate the mechanism of HDAC8 activation. Our results revealed that improper binding of the coumarin group of fluorescent substrates leads to the "flipping out" of catalytic residue Y306, which reduces the enzymatic activity of HDAC8 towards fluorescent substrates. A pocket between the coumarin group of the substrate and thed catalytic residue Y306 was filled with the activator TM-2-51, which not only enhanced binding between HDAC8 and the fluorescent substrate complex but also stabilized Y306 in a catalytically active conformation. Based on this newly proposed substrate-dependent activation mechanism, we performed structure-based virtual screening and successfully identified low-molecular-weight scaffolds as new HDAC8 activators.

Embedded Mean-Field Theory for Solution-Phase Transition-Metal Polyolefin Catalysis

Decreasing the wall-clock time of quantum mechanics/molecular mechanics (QM/MM) calculations without sacrificing accuracy is a crucial prerequisite for widespread simulation of solution-phase dynamical processes. In this work, we demonstrate the use of embedded mean-field theory (EMFT) as the QM engine in QM/MM molecular dynamics (MD) simulations to examine polyolefin catalysts in solution. We show that employing EMFT in this mode preserves the accuracy of hybrid-functional DFT in the QM region, while providing up to 20-fold reductions in the cost per SCF cycle, thereby increasing the accessible simulation time-scales. We find that EMFT reproduces DFT-computed binding energies and optimized bond lengths to within chemical accuracy, as well as consistently ranking conformer stability. Furthermore, solution-phase EMFT/MM simulations provide insight into the interaction strength of strongly coordinating and bulky counterions.

GM-DockZn: a geometry matching-based docking algorithm for zinc proteins

Motivation

Molecular docking is a widely used technique for large-scale virtual screening of the interactions between small-molecule ligands and their target proteins. However, docking methods often perform poorly for metalloproteins due to additional complexity from the three-way interactions among amino-acid residues, metal ions and ligands. This is a significant problem because zinc proteins alone comprise about 10% of all available protein structures in the protein databank. Here, we developed GM-DockZn that is dedicated for ligand docking to zinc proteins. Unlike the existing docking methods developed specifically for zinc proteins, GM-DockZn samples ligand conformations directly using a geometric grid around the ideal zinc-coordination positions of seven discovered coordination motifs, which were found from the survey of known zinc proteins complexed with a single ligand.

Results

GM-DockZn has the best performance in sampling near-native poses with correct coordination atoms and numbers within the top 50 and top 10 predictions when compared to several state-of-the-art techniques. This is true not only for a non-redundant dataset of zinc proteins but also for a homolog set of different ligand and zinc-coordination systems for the same zinc proteins. Similar superior performance of GM-DockZn for near-native-pose sampling was also observed for docking to apo-structures and cross-docking between different ligand complex structures of the same protein. The highest success rate for sampling nearest near-native poses within top 5 and top 1 was achieved by combining GM-DockZn for conformational sampling with GOLD for ranking. The proposed geometry-based sampling technique will be useful for ligand docking to other metalloproteins.

Availability and implementation

GM-DockZn is freely available at www.qmclab.com/ for academic users.

Supplementary information

Supplementary data are available at Bioinformatics online.

User-Friendly Quantum Mechanics: Applications for Drug Discovery

Quantum mechanics (QM) methods provide a fine description of receptor-ligand interactions and of chemical reactions. Their use in drug design and drug discovery is increasing, especially for complex systems including metal ions in the binding sites, for the design of highly selective inhibitors, for the optimization of bi-specific compounds, to understand enzymatic reactions, and for the study of covalent ligands and prodrugs. They are also used for generating molecular descriptors for predictive QSAR/QSPR models and for the parameterization of force fields. Thanks to the continuous increase of computational power offered by GPUs and to the development of sophisticated algorithms, QM methods are becoming part of the standard tools used in computer-aided drug design (CADD). We present the most used QM methods and software packages, and we discuss recent representative applications in drug design and drug discovery.

How to complete the tautomerization and substrate-assisted activation prior to C–C bond fission by meta-cleavage product hydrolase LigY?

Two feasible binding modes could complete the C–C bond fission of the substrate. One is the bidentate mode and five-coordination, and the other is the monodentate mode and five-coordination.

Conformational dynamics and allosteric effect modulated by the unique zinc-binding motif in class IIa HDACs

Class IIa histone deacetylases (HDACs) have been considered as potential targets for the treatment of several diseases. Compared to other HDACs, class IIa HDACs have an additional second zinc binding motif. So far, the function of the unique zinc-binding motif is still not very clear. In this work, extensive classical molecular dynamics (MD) simulations were employed to illuminate the conformational change modulated by the unique zinc-binding motif. It has been revealed that the unique zinc-binding motif is a crucial structural stabilization factor in retaining the catalytic activity of the enzyme and the stability of the multi-protein complex, by remotely modulating the active site pocket in a "closed" conformation. Moreover, it is also revealed that the Loop2 motion in HDAC4 is less flexible than that in HDAC7, which opens a new avenue to design selective inhibitors by utilizing the local conformational dynamics difference between the structurally highly similar HDAC4 and HDAC7. Finally, by comparative studies with class I HDACs (HDAC1-3), it is found that the reversible "in-out" conformational transformation of the binding rail (highly conserved both in class I and IIa HDACs) occurs spontaneously in HDAC1-3, whereas the binding rail is trapped in an "in" conformation owing to the strong metal coordination interaction of the unique CCHC zinc-binding motif in class IIa HDACs. Thus, the CCHC zinc-binding motif may be a feasible allosteric site for the development of class IIa-selective inhibitors.

Ab Initio QM/MM Modeling of the Rate-Limiting Proton Transfer Step in the Deamination of Tryptamine by Aromatic Amine Dehydrogenase

Aromatic amine dehydrogenase (AADH) and related enzymes are at the heart of debates on the roles of quantum tunneling and protein dynamics in catalysis. The reaction of tryptamine in AADH involves significant quantum tunneling in the rate-limiting proton transfer step, shown by large H/D primary kinetic isotope effects (KIEs), with unusual temperature dependence. We apply correlated ab initio combined quantum mechanics/molecular mechanics (QM/MM) methods, at levels up to local coupled cluster theory (LCCSD(T)/(aug)-cc-pVTZ), to calculate accurate potential energy surfaces for this reaction, which are necessary for quantitative analysis of tunneling contributions and reaction dynamics. Different levels of QM/MM treatment are tested. Multiple pathways are calculated with fully flexible transition state optimization by the climbing-image nudged elastic band method at the density functional QM/MM level. The average LCCSD(T) potential energy barriers to proton transfer are 16.7 and 14.0 kcal/mol for proton transfer to the two carboxylate atoms of the catalytic base, Asp128β. The results show that two similar, but distinct pathways are energetically accessible. These two pathways have different barriers, exothermicity and curvature, and should be considered in analyses of the temperature dependence of reaction and KIEs in AADH and other enzymes. These results provide a benchmark for this prototypical enzyme reaction and will be useful for developing empirical models, and analyzing experimental data, to distinguish between different conceptual models of enzyme catalysis.

The uncoupling of autophagy and zinc homeostasis in airway epithelial cells as a fundamental contributor to COPD

The proper regulation of zinc (Zn) trafficking proteins and the cellular distribution of Zn are critical for the maintenance of autophagic processes. However, there have been no studies that have examined Zn dyshomeostasis and the disease-related modulation of autophagy observed in the airways afflicted with chronic obstructive pulmonary disease (COPD). We hypothesized that dysregulated autophagy in airway epithelial cells (AECs) is related to Zn dysregulation in cigarette smoke (CS)-induced COPD. We applied a human ex vivo air-liquid interface model, a murine model of smoke exposure, and human lung tissues and investigated Zn, ZIP1, and ZIP2 Zn-influx proteins, autophagy [microtubule-associated 1A/1B-light chain-3 (LC3), Beclin-1], autophagic flux (Sequestosome), apoptosis [Bcl2; X-linked inhibitor of apoptosis (XIAP), poly (ADP)-ribose polymerase (PARP)], and inflammation [thymic stromal lymphopoietin (TSLP), regulated on activation, normal T cell expressed and secreted (RANTES), and IL-1β]. Lung tissues from CS-exposed mice exhibit reduced free-Zn in AECs, with elevated ZIP1 and diminished ZIP2 expression. Interestingly, increased LC3 colocalized with ZIP1, suggesting an autophagic requirement for free-Zn to support its catabolic function. In human AECs, autophagy was initiated but was unable to efficiently degrade cellular debris, as evidenced by stable Beclin-1 and increased LC3-II, but with a concomitant elevation in Sequestosome. Autophagic dysfunction due to CS exposure coupled with Zn depletion also induced apoptosis, with the reduction of antiapoptotic and antiautophagic proteins Bcl2 and XIAP and PARP cleavage. This was accompanied by an increase in RANTES and TSLP, an activator of adaptive immunity. We conclude that the uncoupling of Zn trafficking and autophagy in AECs constitutes a fundamental disease-related mechanism for COPD pathogenesis and could provide a new therapeutic target.

Design, synthesis and biological evaluation of quinoline derivatives as HDAC class I inhibitors

Inhibition of histone deacetylase (HDAC) has been regarded as a potential therapeutic approach for treatment of multiple diseases including cancer. Based on pharmacophore model of HDAC inhibitors, a series of quinoline-based N-hydroxycinnamamides and N-hydroxybenzamides were designed and synthesized as potent HDAC inhibitors. All target compounds were evaluated for their in vitro HDAC inhibitory activities and anti-proliferative activities and the best compound 4a surpass Vorinostat in both enzymatic inhibitory activity and cellular anti-proliferative activity. In terms of HDAC isoforms selectivity, compounds 4a exhibited preferable inhibition for class I HDACs, especially for HDAC8, the IC₅₀ value (442 nM) was much lower than that of Vorinostat (7468 nM). Subsequently, we performed class I & IIa HDACs whole cell enzyme assay to evaluate inhibitory activity in whole cell context. Compounds 4a and 4e displayed much better cellular activity for class I HDACs than that for class IIa HDACs, which indicated that 4a and 4e might be potent class I HDAC inhibitors. Meanwhile, flow cytometry analysis showed that compound 4a and 4e can promote cell apoptosis in vitro.

The Search for Potent, Small-Molecule HDACIs in Cancer Treatment: A Decade After Vorinostat

Histone deacetylases (HDACs) play a crucial role in the remodeling of chromatin, and are involved in the epigenetic regulation of gene expression. In the last decade, inhibition of HDACs came out as a target for specific epigenetic changes associated with cancer and other diseases. Until now, more than 20 HDAC inhibitors (HDACIs) have entered clinical studies, and some of them (e.g., vorinostat, romidepsin) have been approved for the treatment of cutaneous T-cell lymphoma. This review provides an overview of current knowledge, progress, and molecular mechanisms of HDACIs, covering a period from 2011 until 2015.

Metal Ion Modeling Using Classical Mechanics

Metal ions play significant roles in numerous fields including chemistry, geochemistry, biochemistry, and materials science. With computational tools increasingly becoming important in chemical research, methods have emerged to effectively face the challenge of modeling metal ions in the gas, aqueous, and solid phases. Herein, we review both quantum and classical modeling strategies for metal ion-containing systems that have been developed over the past few decades. This Review focuses on classical metal ion modeling based on unpolarized models (including the nonbonded, bonded, cationic dummy atom, and combined models), polarizable models (e.g., the fluctuating charge, Drude oscillator, and the induced dipole models), the angular overlap model, and valence bond-based models. Quantum mechanical studies of metal ion-containing systems at the semiempirical, ab initio, and density functional levels of theory are reviewed as well with a particular focus on how these methods inform classical modeling efforts. Finally, conclusions and future prospects and directions are offered that will further enhance the classical modeling of metal ion-containing systems.

An Automated Strategy for Binding-Pose Selection and Docking Assessment in Structure-Based Drug Design

Molecular docking is a widely used technique in drug design to predict the binding pose of a candidate compound in a defined therapeutic target. Numerous docking protocols are available, each characterized by different search methods and scoring functions, thus providing variable predictive capability on a same ligand-protein system. To validate a docking protocol, it is necessary to determine a priori the ability to reproduce the experimental binding pose (i.e., by determining the docking accuracy (DA)) in order to select the most appropriate docking procedure and thus estimate the rate of success in docking novel compounds. As common docking programs use generally different root-mean-square deviation (RMSD) formulas, scoring functions, and format results, it is both difficult and time-consuming to consistently determine and compare their predictive capabilities in order to identify the best protocol to use for the target of interest and to extrapolate the binding poses (i.e., best-docked (BD), best-cluster (BC), and best-fit (BF) poses) when applying a given docking program over thousands/millions of molecules during virtual screening. To reduce this difficulty, two new procedures called Clusterizer and DockAccessor have been developed and implemented for use with some common and "free-for-academics" programs such as AutoDock4, AutoDock4(Zn), AutoDock Vina, DOCK, MpSDockZn, PLANTS, and Surflex-Dock to automatically extrapolate BD, BC, and BF poses as well as to perform consistent cluster and DA analyses. Clusterizer and DockAccessor (code available over the Internet) represent two novel tools to collect computationally determined poses and detect the most predictive docking approach. Herein an application to human lysine deacetylase (hKDAC) inhibitors is illustrated.