Impact of ribosomal modification on the binding of the antibiotic telithromycin using a combined grand canonical monte carlo/molecular dynamics simulation approach

A computational workflow to determine drug candidates alternative to aminoglycosides targeting the decoding center of E. coli ribosome

The global antibiotic resistance problem necessitates fast and effective approaches to finding novel inhibitors to treat bacterial infections. In this study, we propose a computational workflow to identify plausible high-affinity compounds from FDA-approved, investigational, and experimental libraries for the decoding center on the small subunit 30S of the E. coli ribosome. The workflow basically consists of two molecular docking calculations on the intact 30S, followed by molecular dynamics (MD) simulations coupled with MM-GBSA calculations on a truncated ribosome structure. The parameters used in the molecular docking suits, Glide and AutoDock Vina, as well as in the MD simulations with Desmond were carefully adjusted to obtain expected interactions for the ligand-rRNA complexes. A filtering procedure was followed, considering a fingerprint based on aminoglycoside's binding site on the 30S to obtain seven hit compounds either with different clinical usages or aminoglycoside derivatives under investigation, suggested for in vitro studies. The detailed workflow developed in this study promises an effective and fast approach for the estimation of binding free energies of large protein-RNA and ligand complexes.

Conformational changes of ribosomes during translation elongation resolved by molecular dynamics simulations

Molecular dynamics simulations have emerged as a powerful set of tools to unravel the intricate dynamics of ribosomes during protein synthesis. Recent advancements in this field have enabled simulations to delve deep into the conformational rearrangements of ribosomes and associated factors, providing invaluable insights into the intricacies of translation. Emphasis on simulations has recently been on translation elongation, such as tRNA selection, translocation, and ribosomal head-swivel motions. These studies have offered crucial structural interpretations of how genetic information is faithfully translated into proteins. This review outlines recent discoveries concerning ribosome conformational changes occurring during translation elongation, as elucidated through molecular dynamics simulations.

The energy landscape of the ribosome

The ribosome is a prototypical assembly that can be used to establish general principles and techniques for the study of biological molecular machines. Motivated by the fact that the dynamics of every biomolecule is governed by an underlying energy landscape, there has been great interest to understand and quantify ribosome energetics. In the present review, we will focus on theoretical and computational strategies for probing the interactions that shape the energy landscape of the ribosome, with an emphasis on more recent studies of the elongation cycle. These efforts include the application of quantum mechanical methods for describing chemical kinetics, as well as classical descriptions to characterize slower (microsecond to millisecond) large-scale (10-100 Å) rearrangements, where motion is described in terms of diffusion across an energy landscape. Together, these studies provide broad insights into the factors that control a diverse range of dynamical processes in this assembly.

Machines on Genes through the Computational Microscope

Macromolecular machines acting on genes are at the core of life's fundamental processes, including DNA replication and repair, gene transcription and regulation, chromatin packaging, RNA splicing, and genome editing. Here, we report the increasing role of computational biophysics in characterizing the mechanisms of "machines on genes", focusing on innovative applications of computational methods and their integration with structural and biophysical experiments. We showcase how state-of-the-art computational methods, including classical and ab initio molecular dynamics to enhanced sampling techniques, and coarse-grained approaches are used for understanding and exploring gene machines for real-world applications. As this review unfolds, advanced computational methods describe the biophysical function that is unseen through experimental techniques, accomplishing the power of the "computational microscope", an expression coined by Klaus Schulten to highlight the extraordinary capability of computer simulations. Pushing the frontiers of computational biophysics toward a pragmatic representation of large multimegadalton biomolecular complexes is instrumental in bridging the gap between experimentally obtained macroscopic observables and the molecular principles playing at the microscopic level. This understanding will help harness molecular machines for medical, pharmaceutical, and biotechnological purposes.

Structure of Erm-modified 70S ribosome reveals the mechanism of macrolide resistance

Many antibiotics inhibit bacterial growth by binding to the ribosome and interfering with protein biosynthesis. Macrolides represent one of the most successful classes of ribosome-targeting antibiotics. The main clinically relevant mechanism of resistance to macrolides is dimethylation of the 23S rRNA nucleotide A2058, located in the drug-binding site, a reaction catalyzed by Erm-type rRNA methyltransferases. Here, we present the crystal structure of the Erm-dimethylated 70S ribosome at 2.4 Å resolution, together with the structures of unmethylated 70S ribosome functional complexes alone or in combination with macrolides. Altogether, our structural data do not support previous models and, instead, suggest a principally new explanation of how A2058 dimethylation confers resistance to macrolides. Moreover, high-resolution structures of two macrolide antibiotics bound to the unmodified ribosome reveal a previously unknown role of the desosamine moiety in drug binding, laying a foundation for the rational knowledge-based design of macrolides that can overcome Erm-mediated resistance.

Advanced Methods for Studying Structure and Interactions of Macrolide Antibiotics

Macrolide antibiotics are macrocyclic compounds that are clinically used and prescribed for the treatment of upper and lower respiratory tract infections. They inhibit the synthesis of bacterial proteins by reversible binding to the 23S rRNA at or near the peptidyl transferase center. However, their excellent antibacterial profile was largely compromised by the emergence of bacterial resistance. Today, fighting resistance to antibiotics is one of the greatest challenges in medicinal chemistry. Considering various physicochemical properties of macrolides, understanding their structure and interactions with macromolecular targets is crucial for the design of new antibiotics efficient against resistant pathogens. The solid-state structures of some macrolide-ribosome complexes have recently been solved, throwing new light on the macrolide binding mechanisms. On the other hand, a combination of NMR spectroscopy and molecular modeling calculations can be applied to study free and bound conformations in solution. In this article, a description of advanced physicochemical methods for elucidating the structure and interactions of macrolide antibiotics in solid state and solution will be provided, and their principal advantages and drawbacks will be discussed.

Erythromycin, Cethromycin and Solithromycin display similar binding affinities to the E. coli's ribosome: A molecular simulation study

Macrolide antibiotics bind to the exit tunnel of the ribosome and inhibit protein synthesis blocking its translocation. Thus, antibiotics including the known macrolide Erythromycin (ERY) are active against bacteria. However, at present, some bacteria show resistance to drugs, which requires the development of new powerful antibacterial agents. One possible way is to use the ERY structure, but change its side chains, while the size of the lactone ring can remain unchanged or change. In this work we consider Cethromycin (CET) and Solithromycin (SOL), which are ketolides with quinolylallyl group at C6 and aminophenyl at C11, respectively (both of them have the same lactone ring as ERY). Experiments have shown that these ketolides have improved efficacy against pathogens, but their binding affinity to the E. coli's ribosome is almost identical. To clarify this issue, we have studied in detail the binding mechanisms of ERY, CET and SOL using the docking and molecular dynamic simulations. In agreement with the experiments, we showed that these compounds have similar binding affinities. Desosamine and lactone ring groups play a critical role in the binding of ERY to the ribosome. In CET and SOL, the contribution of keto and alkylaryl groups is balanced by cyclic carbamate. We have demonstrated that increased fluctuations in the ribosomal residues at the binding site led to an increase in the entropic term in the free binding energy of ERY compared to SOL and CET. The alkyl-aryl arm of both ketolides strongly interacts with A752 and U2609. In addition, the presence of macrolides in the exit tunnel can alter the conformation of U2585, which is located in the peptidyl transferase center, through non-bonded interaction. Therefore, the side chain of ketolides affects not only the binding site but also other residues possibly leading to a strong effect on the protein synthesis process. We predict that to combat bacterial mutations, it is necessary either to design a bulk and charged group as a cladinose, or to use several groups with different signs of charges. This prediction can be used for the development of new efficient antibiotics.

Molecular dynamics simulations suggest why the A2058G mutation in 23S RNA results in bacterial resistance against clindamycin

Clindamycin, a lincosamide antibiotic, binds to 23S ribosomal RNA and inhibits protein synthesis. The A2058G mutation in 23S RNA results in bacterial resistance to clindamycin. To understand the influence of this mutation on short-range interactions of clindamycin with 23S RNA, we carried out full-atom molecular dynamics simulations of a ribosome fragment containing clindamycin binding site. We compared the dynamical behavior of this fragment simulated with and without the A2058G mutation. Molecular dynamics simulations suggest that clindamycin in the native ribosomal binding site is more internally flexible than in the A2058G mutant. Only in the native ribosome fragment did we observe intramolecular conformational change of clindamycin around its C7-N1-C10-C11 dihedral. In the mutant, G2058 makes more stable hydrogen bonds with clindamycin hindering its conformational freedom in the ribosome-bound state. Clindamycin binding site is located in the entrance to the tunnel through which the newly synthesized polypeptide leaves the ribosome. We observed that in the native ribosome fragment, clindamycin blocks the passage in the tunnel entrance, whereas in the mutated fragment the aperture is undisturbed due to a different mode of binding of clindamycin in the mutant. Restricted conformational freedom of clindamycin in a position not blocking the tunnel entrance in the A2058G mutant could explain the molecular mechanism of bacterial resistance against clindamycin occurring in this mutant.

Molecular simulations of the ribosome and associated translation factors

The ribosome is a macromolecular complex which is responsible for protein synthesis in all living cells according to their transcribed genetic information. Using X-ray crystallography and, more recently, cryo-electron microscopy (cryo-EM), the structure of the ribosome was resolved at atomic resolution in many functional and conformational states. Molecular dynamics simulations have added information on dynamics and energetics to the available structural information, thereby have bridged the gap to the kinetics obtained from single-molecule and bulk experiments. Here, we review recent computational studies that brought notable insights into ribosomal structure and function.

Investigation of Ribosomes Using Molecular Dynamics Simulation Methods

The ribosome as a complex molecular machine undergoes significant conformational changes while synthesizing a protein molecule. Molecular dynamics simulations have been used as complementary approaches to X-ray crystallography and cryoelectron microscopy, as well as biochemical methods, to answer many questions that modern structural methods leave unsolved. In this review, we demonstrate that all-atom modeling of ribosome molecular dynamics is particularly useful in describing the process of tRNA translocation, atomic details of behavior of nascent peptides, antibiotics, and other small molecules in the ribosomal tunnel, and the putative mechanism of allosteric signal transmission to functional sites of the ribosome.

Computer-Aided Drug Design Methods

Computational approaches are useful tools to interpret and guide experiments to expedite the antibiotic drug design process. Structure-based drug design (SBDD) and ligand-based drug design (LBDD) are the two general types of computer-aided drug design (CADD) approaches in existence. SBDD methods analyze macromolecular target 3-dimensional structural information, typically of proteins or RNA, to identify key sites and interactions that are important for their respective biological functions. Such information can then be utilized to design antibiotic drugs that can compete with essential interactions involving the target and thus interrupt the biological pathways essential for survival of the microorganism(s). LBDD methods focus on known antibiotic ligands for a target to establish a relationship between their physiochemical properties and antibiotic activities, referred to as a structure-activity relationship (SAR), information that can be used for optimization of known drugs or guide the design of new drugs with improved activity. In this chapter, standard CADD protocols for both SBDD and LBDD will be presented with a special focus on methodologies and targets routinely studied in our laboratory for antibiotic drug discoveries.

Parametrization of macrolide antibiotics using the force field toolkit

Macrolides are an important class of antibiotics that target the bacterial ribosome. Computer simulations of macrolides are limited as specific force field parameters have not been previously developed for them. Here, we determine CHARMM-compatible force field parameters for erythromycin, azithromycin, and telithromycin, using the force field toolkit (ffTK) plugin in VMD. Because of their large size, novel approaches for parametrizing them had to be developed. Two methods for determining partial atomic charges, from interactions with TIP3P water and from the electrostatic potential, as well as several approaches for fitting the dihedral parameters were tested. The performance of the different parameter sets was evaluated by molecular dynamics simulations of the macrolides in ribosome, with a distinct improvement in maintenance of key interactions observed after refinement of the initial parameters. Based on the results of the macrolide tests, recommended procedures for parametrizing very large molecules using ffTK are given.

CHARMM additive and polarizable force fields for biophysics and computer-aided drug design

BACKGROUND

Molecular Mechanics (MM) is the method of choice for computational studies of biomolecular systems owing to its modest computational cost, which makes it possible to routinely perform molecular dynamics (MD) simulations on chemical systems of biophysical and biomedical relevance.

SCOPE OF REVIEW

As one of the main factors limiting the accuracy of MD results is the empirical force field used, the present paper offers a review of recent developments in the CHARMM additive force field, one of the most popular biomolecular force fields. Additionally, we present a detailed discussion of the CHARMM Drude polarizable force field, anticipating a growth in the importance and utilization of polarizable force fields in the near future. Throughout the discussion emphasis is placed on the force fields' parametrization philosophy and methodology.

MAJOR CONCLUSIONS

Recent improvements in the CHARMM additive force field are mostly related to newly found weaknesses in the previous generation of additive force fields. Beyond the additive approximation is the newly available CHARMM Drude polarizable force field, which allows for MD simulations of up to 1μs on proteins, DNA, lipids and carbohydrates.

GENERAL SIGNIFICANCE

Addressing the limitations ensures the reliability of the new CHARMM36 additive force field for the types of calculations that are presently coming into routine computational reach while the availability of the Drude polarizable force fields offers an inherently more accurate model of the underlying physical forces driving macromolecular structures and dynamics. This article is part of a Special Issue entitled "Recent developments of molecular dynamics".

Molecular dynamics simulations of large macromolecular complexes

Connecting dynamics to structural data from diverse experimental sources, molecular dynamics simulations permit the exploration of biological phenomena in unparalleled detail. Advances in simulations are moving the atomic resolution descriptions of biological systems into the million-to-billion atom regime, in which numerous cell functions reside. In this opinion, we review the progress, driven by large-scale molecular dynamics simulations, in the study of viruses, ribosomes, bioenergetic systems, and other diverse applications. These examples highlight the utility of molecular dynamics simulations in the critical task of relating atomic detail to the function of supramolecular complexes, a task that cannot be achieved by smaller-scale simulations or existing experimental approaches alone.

Desmethyl macrolides: synthesis and evaluation of 4-desmethyl telithromycin

Novel sources of antibiotics are needed to address the serious threat of bacterial resistance. Accordingly, we have launched a structure-based drug design program featuring a desmethylation strategy wherein methyl groups have been replaced with hydrogens. Herein we report the total synthesis, molecular modeling, and biological evaluation of 4-desmethyl telithromycin (6), a novel desmethyl analogue of the third-generation ketolide antibiotic telithromycin (2) and our final analogue in this series. While 4-desmethyl telithromycin (6) was found to be equipotent with telithromycin (2) against wild-type bacteria, it was 4-fold less potent against the A2058G mutant. These findings reveal that strategically replacing the C4-methyl group with hydrogen (i.e., desmethylation) did not address this mechanism of resistance. Throughout the desmethyl series, the sequential addition of methyls to the 14-membered macrolactone resulted in improved bioactivity. Molecular modeling methods indicate that changes in conformational flexibility dominate the increased biological activity; moreover, they reveal 6 adopts a different conformation once bound to the A2058G ribosome, thus impacting noncovalent interactions reflected in a lower MIC value. Finally, fluorescence polarization experiments of 6 with E. coli ribosomes confirmed 6 is indeed binding the ribosome.

Sampling of Organic Solutes in Aqueous and Heterogeneous Environments Using Oscillating Excess Chemical Potentials in Grand Canonical-like Monte Carlo-Molecular Dynamics Simulations

Solute sampling of explicit bulk-phase aqueous environments in grand canonical (GC) ensemble simulations suffer from poor convergence due to low insertion probabilities of the solutes. To address this, we developed an iterative procedure involving Grand Canonical-like Monte Carlo (GCMC) and molecular dynamics (MD) simulations. Each iteration involves GCMC of both the solutes and water followed by MD, with the excess chemical potential (μ_ex) of both the solute and the water oscillated to attain their target concentrations in the simulation system. By periodically varying the μ_ex of the water and solutes over the GCMC-MD iterations, solute exchange probabilities and the spatial distributions of the solutes improved. The utility of the oscillating-μ_ex GCMC-MD method is indicated by its ability to approximate the hydration free energy (HFE) of the individual solutes in aqueous solution as well as in dilute aqueous mixtures of multiple solutes. For seven organic solutes: benzene, propane, acetaldehyde, methanol, formamide, acetate, and methylammonium, the average μ_ex of the solutes and the water converged close to their respective HFEs in both 1 M standard state and dilute aqueous mixture systems. The oscillating-μ_ex GCMC methodology is also able to drive solute sampling in proteins in aqueous environments as shown using the occluded binding pocket of the T4 lysozyme L99A mutant as a model system. The approach was shown to satisfactorily reproduce the free energy of binding of benzene as well as sample the functional group requirements of the occluded pocket consistent with the crystal structures of known ligands bound to the L99A mutant as well as their relative binding affinities.

Desmethyl Macrolides: Synthesis and Evaluation of 4,8,10-Tridesmethyl Cethromycin

Antibiotic-resistant bacteria are emerging at an alarming rate in both hospital and community settings. Motivated by this issue, we have prepared desmethyl (i.e., replacing methyl groups with hydrogens) analogues of third-generation macrolide drugs telithromycin (TEL, 2) and cethromycin (CET, 6), both of which are semi-synthetic derivatives of flagship macrolide antibiotic erythromycin (1). Herein, we report the total synthesis, molecular modeling, and biological evaluation of 4,8,10-tridesmethyl cethromycin (7). In MIC assays, CET analogue 7 was found to be equipotent with TEL (2) against a wild-type E. coli strain, more potent than previously disclosed desmethyl TEL congeners 3, 4, and 5, but fourfold less potent than TEL (2) against a mutant E. coli A2058G strain.