Automated cryo-EM structure refinement using correlation-driven molecular dynamics

Comparison of CryoEM and X-ray structures of dimethylformamidase

Dimethylformamidase (DMFase) catalyzes the hydrolysis of dimethylformamide, an industrial solvent, introduced into the environment by humans. Recently, we determined the structures of dimethylformamidase by electron cryo microscopy and X-ray crystallography revealing a tetrameric enzyme with a mononuclear iron at the active site. DMFase from Paracoccus sp. isolated from a waste water treatment plant around the city of Kanpur in India shows maximal activity at 54 °C and is halotolerant. The structures determined by both techniques are mostly identical and the largest difference is in a loop near the active site. This loop could play a role in co-operativity between the monomers. A number of non-protein densities are observed in the EM map, which are modelled as water molecules. Comparison of the structures determined by the two methods reveals conserved water molecules that could play a structural role. The higher stability, unusual active site and negligible activity at low temperature makes this a very good model to study enzyme mechanism by cryoEM.

Advances in methods for atomic resolution macromolecular structure determination

Recent technical advances have dramatically increased the power and scope of structural biology. New developments in high-resolution cryo-electron microscopy, serial X-ray crystallography, and electron diffraction have been especially transformative. Here we highlight some of the latest advances and current challenges at the frontiers of atomic resolution methods for elucidating the structures and dynamical properties of macromolecules and their complexes.

Structure and Dynamics in the ATG8 Family From Experimental to Computational Techniques

Autophagy is a conserved and essential intracellular mechanism for the removal of damaged components. Since autophagy deregulation is linked to different kinds of pathologies, it is fundamental to gain knowledge on the fine molecular and structural details related to the core proteins of the autophagy machinery. Among these, the family of human ATG8 proteins plays a central role in recruiting other proteins to the different membrane structures involved in the autophagic pathway. Several experimental structures are available for the members of the ATG8 family alone or in complex with their different biological partners, including disordered regions of proteins containing a short linear motif called LC3 interacting motif. Recently, the first structural details of the interaction of ATG8 proteins with biological membranes came into light. The availability of structural data for human ATG8 proteins has been paving the way for studies on their structure-function-dynamic relationship using biomolecular simulations. Experimental and computational structural biology can help to address several outstanding questions on the mechanism of human ATG8 proteins, including their specificity toward different interactors, their association with membranes, the heterogeneity of their conformational ensemble, and their regulation by post-translational modifications. We here summarize the main results collected so far and discuss the future perspectives within the field and the knowledge gaps. Our review can serve as a roadmap for future structural and dynamics studies of the ATG8 family members in health and disease.

Enhanced sampling and free energy calculations for protein simulations

Molecular dynamics simulation is a powerful computational technique to study biomolecular systems, which complements experiments by providing insights into the structural dynamics relevant to biological functions at atomic scale. It can also be used to calculate the free energy landscapes of the conformational transitions to better understand the functions of the biomolecules. However, the sampling of biomolecular configurations is limited by the free energy barriers that need to be overcome, leading to considerable gaps between the timescales reached by MD simulation and those governing biological processes. To address this issue, many enhanced sampling methodologies have been developed to increase the sampling efficiency of molecular dynamics simulations and free energy calculations. Usually, enhanced sampling algorithms can be classified into methods based on collective variables (CV-based) and approaches which do not require predefined CVs (CV-free). In this chapter, the theoretical basis of free energy estimation is briefly reviewed first, followed by the reviews of the most common CV-based and CV-free methods including the presentation of some examples and recent developments. Finally, the combination of different enhanced sampling methods is discussed.

A Refined Open State of the Glycine Receptor Obtained via Molecular Dynamics Simulations

Pentameric ligand-gated ion channels are key players in mediating fast neurotransmission. Glycine receptors are chloride-selective members of this receptor family that mediate inhibitory synaptic transmission and are implicated in neurological disorders including autism and hyperekplexia. They have been structurally characterized by both X-ray crystallography and cryoelectron microscopy (cryo-EM) studies, with the latter giving rise to what was proposed as a possible open state. However, recent work has questioned the physiological relevance of this open state structure, since it rapidly collapses in molecular dynamics simulations. Here, we show that the collapse can be avoided by a careful equilibration protocol that reconciles the more problematic regions of the original density map and gives a stable open state that shows frequent selective chloride permeation. The protocol developed in this work provides a means to refine open-like structures of the whole pentameric ligand-gated ion channel superfamily and reconciles the previous issues with the cryo-EM structure.

Advances in Structure Modeling Methods for Cryo-Electron Microscopy Maps

Cryo-electron microscopy (cryo-EM) has now become a widely used technique for structure determination of macromolecular complexes. For modeling molecular structures from density maps of different resolutions, many algorithms have been developed. These algorithms can be categorized into rigid fitting, flexible fitting, and de novo modeling methods. It is also observed that machine learning (ML) techniques have been increasingly applied following the rapid progress of the ML field. Here, we review these different categories of macromolecule structure modeling methods and discuss their advances over time.

Cryo_fit: Democratization of flexible fitting for cryo-EM

Cryo-electron microscopy (cryo-EM) is becoming a method of choice for describing native conformations of biomolecular complexes at high resolution. The rapid growth of cryo-EM in recent years has created a high demand for automated solutions, both in hardware and software. Flexible fitting of atomic models to three-dimensional (3D) cryo-EM reconstructions by molecular dynamics (MD) simulation is a popular technique but often requires technical expertise in computer simulation. This work introduces cryo_fit, a package for the automatic flexible fitting of atomic models in cryo-EM maps using MD simulation. The package is integrated with the Phenix software suite. The module was designed to automate the multiple steps of MD simulation in a reproducible manner, as well as facilitate refinement and validation through Phenix. Through the use of cryo_fit, scientists with little experience in MD simulation can produce high quality atomic models automatically and better exploit the potential of cryo-EM.

CryoEM maps are full of potential

Electron microscopy is based on elastic scattering due to Coulomb forces between the incident electrons and the sample; thus, electron scattering is dependent on the charge distribution in the sample. Unlike atomic scattering factors for X-rays, electron scattering factors for some atoms are strongly dependent on scattering angle, and the scattering factor for ionic oxygen is negative at low scattering angle. This phenomenon can result in a significant negative contribution to Coulomb potential maps by oxygen and can result in deviations in the positions of positive map features from atomic centers. An important factor that can also complicate the interpretation of cryoEM maps is the exquisite sensitivity of macromolecules to damage from electron irradiation, especially the carboxylates of acidic amino acids. Ideally, when compared with electron density maps derived by X-ray crystallography, Coulomb potential maps can provide additional details about the electrostatic environment and charge state of atoms. Enhancements in model building, refinement and computational simulation will be required to realize the full potential of EM-derived maps to reveal deeper insight into the electronic structure and functional properties of macromolecular complexes and their interactions with binding partners, ligands, cofactors, and drugs.