Concerted hydrogen atom and electron transfer mechanism for catalysis by lysine-specific demethylase

The structural basis of histone modifying enzyme specificity and promiscuity: Implications for metabolic regulation and drug design

Histone modifying enzymes regulate chromatin architecture through covalent modifications and ultimately control multiple aspects of cellular function. Disruption of histone modification leads to changes in gene expression profiles and may lead to disease. Both small molecule inhibitors and intermediary metabolites have been shown to modulate histone modifying enzyme activity although our ability to identify successful drug candidates or novel metabolic regulators of these enzymes has been limited. Using a combination of large scale in silico screens and in vivo phenotypic analysis, we identified several small molecules and intermediary metabolites with distinctive HME activity. Our approach using unsupervised learning identifies the chemical fingerprints of both small molecules and metabolites that facilitate recognition by the enzymes active sites which can be used as a blueprint to design novel inhibitors. Furthermore, this work supports the idea that histone modifying enzymes sense intermediary metabolites integrating genes, environment and cellular physiology.

Nuclear quantum effects in enzymatic reactions: simulation of the kinetic isotope effect of phenylethylamine oxidation catalyzed by monoamine oxidase A

By using computational techniques for quantizing nuclear motion one can accurately reproduce kinetic isotope effect of enzymatic reactions, as demonstrated for phenylethylamine oxidation catalyzed by the monoamine oxidase A enzyme.

Theoretical approaches for dynamical ordering of biomolecular systems

BACKGROUND

Living systems are characterized by the dynamic assembly and disassembly of biomolecules. The dynamical ordering mechanism of these biomolecules has been investigated both experimentally and theoretically. The main theoretical approaches include quantum mechanical (QM) calculation, all-atom (AA) modeling, and coarse-grained (CG) modeling. The selected approach depends on the size of the target system (which differs among electrons, atoms, molecules, and molecular assemblies). These hierarchal approaches can be combined with molecular dynamics (MD) simulation and/or integral equation theories for liquids, which cover all size hierarchies.

SCOPE OF REVIEW

We review the framework of quantum mechanical/molecular mechanical (QM/MM) calculations, AA MD simulations, CG modeling, and integral equation theories. Applications of these methods to the dynamical ordering of biomolecular systems are also exemplified.

MAJOR CONCLUSIONS

The QM/MM calculation enables the study of chemical reactions. The AA MD simulation, which omits the QM calculation, can follow longer time-scale phenomena. By reducing the number of degrees of freedom and the computational cost, CG modeling can follow much longer time-scale phenomena than AA modeling. Integral equation theories for liquids elucidate the liquid structure, for example, whether the liquid follows a radial distribution function.

GENERAL SIGNIFICANCE

These theoretical approaches can analyze the dynamic behaviors of biomolecular systems. They also provide useful tools for exploring the dynamic ordering systems of biomolecules, such as self-assembly. This article is part of a Special Issue entitled "Biophysical Exploration of Dynamical Ordering of Biomolecular Systems" edited by Dr. Koichi Kato.

Including Memory Friction in Single- and Two-State Quantum Dynamics Simulations

We present a simple computational algorithm that allows for the inclusion of memory friction in a quantum dynamics simulation of a small, quantum, primary system coupled to many atoms in the surroundings. We show how including a memory friction operator, F̂, in the primary quantum system's Hamiltonian operator builds memory friction into the dynamics of the primary quantum system. We show that, in the harmonic, semi-classical limit, this friction operator causes the classical phase-space centers of a wavepacket to evolve exactly as if it were a classical particle experiencing memory friction. We also show that this friction operator can be used to include memory friction in the quantum dynamics of an anharmonic primary system. We then generalize the algorithm so that it can be used to treat a primary quantum system that is evolving, non-adiabatically on two coupled potential energy surfaces, i.e., a model that can be used to model H atom transfer, for example. We demonstrate this approach's computational ease and flexibility by showing numerical results for both harmonic and anharmonic primary quantum systems in the single surface case. Finally, we present numerical results for a model of non-adiabatic H atom transfer between a reactant and product state that includes memory friction on one or both of the non-adiabatic potential energy surfaces and uncover some interesting dynamical effects of non-memory friction on the H atom transfer process.

A Systematic Review of Histone Lysine-Specific Demethylase 1 and Its Inhibitors

Histone lysine-specific demethylase 1 (LSD1) is the first discovered and reported histone demethylase by Dr. Shi Yang's group in 2004. It is classified as a member of amine oxidase superfamily, the common feature of which is using the flavin adenine dinucleotide (FAD) as its cofactor. Since it is located in cell nucleus and acts as a histone methylation eraser, LSD1 specifically removes mono- or dimethylated histone H3 lysine 4 (H3K4) and H3 lysine 9 (H3K9) through formaldehyde-generating oxidation. It has been indicated that LSD1 and its downstream targets are involved in a wide range of biological courses, including embryonic development and tumor-cell growth and metastasis. LSD1 has been reported to be overexpressed in variety of tumors. Inactivating LSD1 or downregulating its expression inhibits cancer-cell development. LSD1 targeting inhibitors may represent a new insight in anticancer drug discovery. This review summarizes recent studies about LSD1 and mainly focuses on the basic physiological function of LSD1 and its involved mechanisms in pathophysiologic conditions, as well as the development of LSD1 inhibitors as potential anticancer therapeutic agents.

KDM1 class flavin-dependent protein lysine demethylases

Flavin-dependent, lysine-specific protein demethylases (KDM1s) are a subfamily of amine oxidases that catalyze the selective posttranslational oxidative demethylation of methyllysine side chains within protein and peptide substrates. KDM1s participate in the widespread epigenetic regulation of both normal and disease state transcriptional programs. Their activities are central to various cellular functions, such as hematopoietic and neuronal differentiation, cancer proliferation and metastasis, and viral lytic replication and establishment of latency. Interestingly, KDM1s function as catalytic subunits within complexes with coregulatory molecules that modulate enzymatic activity of the demethylases and coordinate their access to specific substrates at distinct sites within the cell and chromatin. Although several classes of KDM1-selective small molecule inhibitors have been recently developed, these pan-active site inhibition strategies lack the ability to selectively discriminate between KDM1 activity in specific, and occasionally opposing, functional contexts within these complexes. Here we review the discovery of this class of demethylases, their structures, chemical mechanisms, and specificity. Additionally, we review inhibition of this class of enzymes as well as emerging interactions with coregulatory molecules that regulate demethylase activity in highly specific functional contexts of biological and potential therapeutic importance.

Epigenetic molecular recognition: a biomolecular modeling perspective

The abnormal regulation of epigenetic protein families is associated with the onset and progression of various human diseases. However, epigenetic processes remain relatively obscure at the molecular level, thus preventing the rational design of chemical therapeutics. An array of robust computational and modeling approaches can complement experiments to shed light on the complex mechanisms of epigenetic molecular recognition and can guide medicinal chemists in designing selective and potent drug molecules. Herein we present a review of studies focused on epigenetic molecular recognition from a biomolecular modeling viewpoint. Although the known epigenetic targets are numerous, this review focuses on the more limited protein families on which computational modeling has been successfully applied. Therefore, we review three main topics: 1) histone deacetylases, 2) histone demethylases, and 3) histone tail dynamics. A brief review of the biological background and biomedical relevance is presented for each topic, followed by a detailed discussion of the computational studies and their relevance.

Histone lysine demethylases as targets for anticancer therapy

It has recently been demonstrated that the genes controlling the epigenetic programmes that are required for maintaining chromatin structure and cell identity include genes that drive human cancer. This observation has led to an increased awareness of chromatin-associated proteins as potentially interesting drug targets. The successful introduction of DNA methylation and histone deacetylase (HDAC) inhibitors for the treatment of specific subtypes of cancer has paved the way for the use of epigenetic therapy. Here, we highlight key biological findings demonstrating the roles of members of the histone lysine demethylase class of enzymes in the development of cancers, discuss the potential and challenges of therapeutically targeting them, and highlight emerging small-molecule inhibitors of these enzymes.