Molecular Dynamics to Predict Cryo-EM: Capturing Transitions and Short-Lived Conformational States of Biomolecules

Bayesian reweighting of biomolecular structural ensembles using heterogeneous cryo-EM maps with the cryoENsemble method

Cryogenic electron microscopy (cryo-EM) has emerged as a powerful method for the determination of structures of complex biological molecules. The accurate characterisation of the dynamics of such systems, however, remains a challenge. To address this problem, we introduce cryoENsemble, a method that applies Bayesian reweighting to conformational ensembles derived from molecular dynamics simulations to improve their agreement with cryo-EM data, thus enabling the extraction of dynamics information. We illustrate the use of cryoENsemble to determine the dynamics of the ribosome-bound state of the co-translational chaperone trigger factor (TF). We also show that cryoENsemble can assist with the interpretation of low-resolution, noisy or unaccounted regions of cryo-EM maps. Notably, we are able to link an unaccounted part of the cryo-EM map to the presence of another protein (methionine aminopeptidase, or MetAP), rather than to the dynamics of TF, and model its TF-bound state. Based on these results, we anticipate that cryoENsemble will find use for challenging heterogeneous cryo-EM maps for biomolecular systems encompassing dynamic components.

Cryo-EM structure and B-factor refinement with ensemble representation

Cryo-EM experiments produce images of macromolecular assemblies that are combined to produce three-dimensional density maps. Typically, atomic models of the constituent molecules are fitted into these maps, followed by a density-guided refinement. We introduce TEMPy-ReFF, a method for atomic structure refinement in cryo-EM density maps. Our method represents atomic positions as components of a Gaussian mixture model, utilising their variances as B-factors, which are used to derive an ensemble description. Extensively tested on a substantial dataset of 229 cryo-EM maps from EMDB ranging in resolution from 2.1-4.9 Å with corresponding PDB and CERES atomic models, our results demonstrate that TEMPy-ReFF ensembles provide a superior representation of cryo-EM maps. On a single-model basis, it performs similarly to the CERES re-refinement protocol, although there are cases where it provides a better fit to the map. Furthermore, our method enables the creation of composite maps free of boundary artefacts. TEMPy-ReFF is useful for better interpretation of flexible structures, such as those involving RNA, DNA or ligands.

Visualizing the DNA repair process by a photolyase at atomic resolution

Photolyases, a ubiquitous class of flavoproteins, use blue light to repair DNA photolesions. In this work, we determined the structural mechanism of the photolyase-catalyzed repair of a cyclobutane pyrimidine dimer (CPD) lesion using time-resolved serial femtosecond crystallography (TR-SFX). We obtained 18 snapshots that show time-dependent changes in four reaction loci. We used these results to create a movie that depicts the repair of CPD lesions in the picosecond-to-nanosecond range, followed by the recovery of the enzymatic moieties involved in catalysis, completing the formation of the fully reduced enzyme-product complex at 500 nanoseconds. Finally, back-flip intermediates of the thymine bases to reanneal the DNA were captured at 25 to 200 microseconds. Our data cover the complete molecular mechanism of a photolyase and, importantly, its chemistry and enzymatic catalysis at work across a wide timescale and at atomic resolution.

Conformational plasticity and allosteric communication networks explain Shelterin protein TPP1 binding to human telomerase

The Shelterin complex protein TPP1 interacts with human telomerase (TERT) by means of the TEL-patch region, controlling telomere homeostasis. Aberrations in the TPP1-TERT heterodimer formation might lead to short telomeres and severe diseases like dyskeratosis congenita and Hoyeraal-Hreidarsson syndrome. In the present study, we provide a thorough characterization of the structural properties of the TPP1's OB-domain by combining data coming from microsecond-long molecular dynamics calculations, time-series analyses, and graph-based networks. Our results show that the TEL-patch conformational freedom is influenced by a network of long-range amino acid communications that together determine the proper TPP1-TERT binding. Furthermore, we reveal that in TPP1 pathological variants Glu169Δ, Lys170Δ and Leu95Gln, the TEL-patch plasticity is reduced, affecting the correct binding to TERT and, in turn, telomere processivity, which eventually leads to accelerated aging of affected cells. Our study provides a structural basis for the design of TPP1-targeting ligands with therapeutic potential against cancer and telomeropathies.

Fostering discoveries in the era of exascale computing: How the next generation of supercomputers empowers computational and experimental biophysics alike

Over a century ago, physicists started broadly relying on theoretical models to guide new experiments. Soon thereafter, chemists began doing the same. Now, biological research enters a new era when experiment and theory walk hand in hand. Novel software and specialized hardware became essential to understand experimental data and propose new models. In fact, current petascale computing resources already allow researchers to reach unprecedented levels of simulation throughput to connect in silico and in vitro experiments. The reduction in cost and improved access allowed a large number of research groups to adopt supercomputing resources and techniques. Here, we outline how large-scale computing has evolved to expand decades-old research, spark new research efforts, and continuously connect simulation and observation. For instance, multiple publicly and privately funded groups have dedicated extensive resources to develop artificial intelligence tools for computational biophysics, from accelerating quantum chemistry calculations to proposing protein structure models. Moreover, advances in computer hardware have accelerated data processing from single-molecule experimental observations and simulations of chemical reactions occurring throughout entire cells. The combination of software and hardware has opened the way for exascale computing and the production of the first public exascale supercomputer, Frontier, inaugurated by the Oak Ridge National Laboratory in 2022. Ultimately, the popularization and development of computational techniques and the training of researchers to use them will only accelerate the diversification of tools and learning resources for future generations.

Million-atom molecular dynamics simulations reveal the interfacial interactions and assembly of plant PSII-LHCII supercomplex

Protein-protein interface interactions dictate efficient excitation energy transfer from light-harvesting antennas to the photosystem II (PSII) core. In this work, we construct a 1.2 million atom-scale model of plant C₂S₂-type PSII-LHCII supercomplex and perform microsecond-scale molecular dynamics (MD) simulations to explore the interactions and assembly mechanisms of the sizeable PSII-LHCII supercomplex. We optimize the nonbonding interactions of the PSII-LHCII cryo-EM structure using microsecond-scale MD simulations. Binding free energy calculations with component decompositions reveal that hydrophobic interactions predominantly drive antenna-core association and the antenna-antenna interactions are relatively weak. Despite the positive electrostatic interaction energies, hydrogen bonds and salt bridges mainly provide directional or anchoring forces for interface binding. Analysis of the roles of small intrinsic subunits of PSII suggests that LHCII and CP26 first interact with small intrinsic subunits and then bind to the core proteins, whereas CP29 adopts a one-step binding process to the PSII core without the assistance of other factors. Our study provides insights into the molecular underpinnings of the self-organization and regulation of plant PSII-LHCII. It lays the framework for deciphering the general assembly principles of photosynthetic supercomplexes and possibly other macromolecular structures. The finding also has implications for repurposing photosynthetic systems to enhance photosynthesis.

Structural biology of CRISPR-Cas immunity and genome editing enzymes

CRISPR-Cas systems provide resistance against foreign mobile genetic elements and have a wide range of genome editing and biotechnological applications. In this Review, we examine recent advances in understanding the molecular structures and mechanisms of enzymes comprising bacterial RNA-guided CRISPR-Cas immune systems and deployed for wide-ranging genome editing applications. We explore the adaptive and interference aspects of CRISPR-Cas function as well as open questions about the molecular mechanisms responsible for genome targeting. These structural insights reflect close evolutionary links between CRISPR-Cas systems and mobile genetic elements, including the origins and evolution of CRISPR-Cas systems from DNA transposons, retrotransposons and toxin-antitoxin modules. We discuss how the evolution and structural diversity of CRISPR-Cas systems explain their functional complexity and utility as genome editing tools.

Geneticin shows selective antiviral activity against SARS-CoV-2 by interfering with programmed -1 ribosomal frameshifting

SARS-CoV-2 is currently causing an unprecedented pandemic. While vaccines are massively deployed, we still lack effective large-scale antiviral therapies. In the quest for antivirals targeting conserved structures, we focused on molecules able to bind viral RNA secondary structures. Aminoglycosides are a class of antibiotics known to interact with the ribosomal RNA of both prokaryotes and eukaryotes and have previously been shown to exert antiviral activities by interacting with viral RNA. Here we show that the aminoglycoside geneticin is endowed with antiviral activity against all tested variants of SARS-CoV-2, in different cell lines and in a respiratory tissue model at non-toxic concentrations. The mechanism of action is an early inhibition of RNA replication and protein expression related to a decrease in the efficiency of the -1 programmed ribosomal frameshift (PRF) signal of SARS-CoV-2. Using in silico modelling, we have identified a potential binding site of geneticin in the pseudoknot of frameshift RNA motif. Moreover, we have selected, through virtual screening, additional RNA binding compounds, interacting with the same site with increased potency.

Intrinsically disordered proteins: Ensembles at the limits of Anfinsen's dogma

Intrinsically disordered proteins (IDPs) are proteins that lack rigid 3D structure. Hence, they are often misconceived to present a challenge to Anfinsen's dogma. However, IDPs exist as ensembles that sample a quasi-continuum of rapidly interconverting conformations and, as such, may represent proteins at the extreme limit of the Anfinsen postulate. IDPs play important biological roles and are key components of the cellular protein interaction network (PIN). Many IDPs can interconvert between disordered and ordered states as they bind to appropriate partners. Conformational dynamics of IDPs contribute to conformational noise in the cell. Thus, the dysregulation of IDPs contributes to increased noise and "promiscuous" interactions. This leads to PIN rewiring to output an appropriate response underscoring the critical role of IDPs in cellular decision making. Nonetheless, IDPs are not easily tractable experimentally. Furthermore, in the absence of a reference conformation, discerning the energy landscape representation of the weakly funneled IDPs in terms of reaction coordinates is challenging. To understand conformational dynamics in real time and decipher how IDPs recognize multiple binding partners with high specificity, several sophisticated knowledge-based and physics-based in silico sampling techniques have been developed. Here, using specific examples, we highlight recent advances in energy landscape visualization and molecular dynamics simulations to discern conformational dynamics and discuss how the conformational preferences of IDPs modulate their function, especially in phenotypic switching. Finally, we discuss recent progress in identifying small molecules targeting IDPs underscoring the potential therapeutic value of IDPs. Understanding structure and function of IDPs can not only provide new insight on cellular decision making but may also help to refine and extend Anfinsen's structure/function paradigm.

Twisting and swiveling domain motions in Cas9 to recognize target DNA duplexes, make double-strand breaks, and release cleaved duplexes

The CRISPR-associated protein 9 (Cas9) has been engineered as a precise gene editing tool to make double-strand breaks. CRISPR-associated protein 9 binds the folded guide RNA (gRNA) that serves as a binding scaffold to guide it to the target DNA duplex via a RecA-like strand-displacement mechanism but without ATP binding or hydrolysis. The target search begins with the protospacer adjacent motif or PAM-interacting domain, recognizing it at the major groove of the duplex and melting its downstream duplex where an RNA-DNA heteroduplex is formed at nanomolar affinity. The rate-limiting step is the formation of an R-loop structure where the HNH domain inserts between the target heteroduplex and the displaced non-target DNA strand. Once the R-loop structure is formed, the non-target strand is rapidly cleaved by RuvC and ejected from the active site. This event is immediately followed by cleavage of the target DNA strand by the HNH domain and product release. Within CRISPR-associated protein 9, the HNH domain is inserted into the RuvC domain near the RuvC active site via two linker loops that provide allosteric communication between the two active sites. Due to the high flexibility of these loops and active sites, biophysical techniques have been instrumental in characterizing the dynamics and mechanism of the CRISPR-associated protein 9 nucleases, aiding structural studies in the visualization of the complete active sites and relevant linker structures. Here, we review biochemical, structural, and biophysical studies on the underlying mechanism with emphasis on how CRISPR-associated protein 9 selects the target DNA duplex and rejects non-target sequences.

Multiscale computational study of ligand binding pathways: Case of p38 MAP kinase and its inhibitors

Protein kinases are one of the most important drug targets in the past 10 years. Understanding the inhibitor association processes will profoundly impact new binder designs with preferred binding kinetics. However, after more than a decade of effort, a complete atomistic-level study of kinase inhibitor binding pathways is still lacking. As all kinases share a similar scaffold, we used p38 kinase as a model system to investigate the conformational dynamics and free energy transition of inhibitor binding toward kinases. Two major kinase conformations, Asp-Phe-Gly (DFG)-in and DFG-out, and three types of inhibitors, type I, II, and III, were thoroughly investigated in this work. We performed Brownian dynamics simulations and up to 340 μs Gaussian-accelerated molecular dynamics simulations to capture the inhibitor binding paths and a series of conformational transitions of the p38 kinase from its apo to inhibitor-bound form. Eighteen successful binding trajectories, including all types of inhibitors, are reported herein. Our simulations suggest a mechanism of inhibitor recruitment, a faster ligand association step to a pre-existing DFG-in/DFG-out p38 protein, followed by a slower molecular rearrangement step to adjust the protein-ligand conformation followed by a shift in the energy landscape to reach the final bound state. The ligand association processes also reflect the energetic favor of type I and type II/III inhibitor binding through ATP and allosteric channels, respectively. These different binding routes are directly responsible for the fast (type I binders) and slow (type II/III binders) kinetics of different types of p38 inhibitors. Our findings also echo the recent study of p38 inhibitor dissociation, implying that ligand unbinding could undergo a reverse path of binding, and both processes share similar metastates. This study deepens the understanding of molecular and energetic features of kinase inhibitor-binding processes and will inspire future drug development from a kinetic point of view.