The Adaptively Biased Molecular Dynamics method revisited: New capabilities and an application

Ins and Outs of Rocker Switch Mechanism in Major Facilitator Superfamily of Transporters

The major facilitator superfamily (MFS) of transporters consists of three classes of membrane transporters: symporters, uniporters, and antiporters. Despite such diverse functions, MFS transporters are believed to undergo similar conformational changes within their distinct transport cycles, known as the rocker-switch mechanism. While the similarities between conformational changes are noteworthy, the differences are also important since they could potentially explain the distinct functions of symporters, uniporters, and antiporters of the MFS superfamily. We reviewed a variety of experimental and computational structural data on a select number of antiporters, symporters, and uniporters from the MFS family to compare the similarities and differences of the conformational dynamics of three different classes of transporters.

Efficient Interrogation of the Kinetic Barriers Demarcating Catalytic States of a Tyrosine Kinase with Optimal Physical Descriptors and Mixture Models

Computer simulations are increasingly used to access thermo-kinetic information underlying structural transformation of protein kinases. Such information are necessary to probe their roles in disease progression and interactions with drug targets. However, the investigations are frequently challenged by forbiddingly high computational expense, and by the lack of standard protocols for the design of low dimensional physical descriptors that encode system features important for transitions. Here, we consider the demarcating characteristics of the different states of Abelson tyrosine kinase associated with distinct catalytic activity to construct a set of physically meaningful, orthogonal collective variables that preserve the slow modes of the system. Independent sampling of each metastable state is followed by the estimation of global partition function along the appropriate physical descriptors using the modified Expectation Maximized Molecular Dynamics method. The resultant free energy barriers are in excellent agreement with experimentally known rate-limiting dynamics and activation energy computed with conventional enhanced sampling methods. We discuss possible directions for further development and applications.

Cholesterol in Class C GPCRs: Role, Relevance, and Localization

G-protein coupled receptors (GPCRs), one of the largest superfamilies of cell-surface receptors, are heptahelical integral membrane proteins that play critical roles in virtually every organ system. G-protein-coupled receptors operate in membranes rich in cholesterol, with an imbalance in cholesterol level within the vicinity of GPCR transmembrane domains affecting the structure and/or function of many GPCRs, a phenomenon that has been linked to several diseases. These effects of cholesterol could result in indirect changes by altering the mechanical properties of the lipid environment or direct changes by binding to specific sites on the protein. There are a number of studies and reviews on how cholesterol modulates class A GPCRs; however, this area of study is yet to be explored for class C GPCRs, which are characterized by a large extracellular region and often form constitutive dimers. This review highlights specific sites of interaction, functions, and structural dynamics involved in the cholesterol recognition of the class C GPCRs. We summarize recent data from some typical family members to explain the effects of membrane cholesterol on the structural features and functions of class C GPCRs and speculate on their corresponding therapeutic potential.

Sarcin/Ricin Domain RNA Retains Its Structure Better Than A-RNA in Adaptively Biased Molecular Dynamics Simulations

Less than one in thirty of the RNA sequences transcribed in humans are translated into protein. The noncoding RNA (ncRNA) functions in catalysis, structure, regulation, and more. However, for the most part, these functions are poorly characterized. RNA is modular and described by motifs that include helical A-RNA with canonical Watson-Crick base-pairing as well as structures with only noncanonical base pairs. Understanding the structure and dynamics of motifs will aid in deciphering functions of specific ncRNAs. We present computational studies on a standard sarcin/ricin domain (SRD), citrus bark cracking viroid SRD, as well as A-RNA. We have applied enhanced molecular dynamics techniques that construct an inverse free-energy surface (iFES) determined by collective variables that monitor base-pairing and backbone conformation. Each SRD RNA is flanked on each side by A-RNA, allowing comparison of the behavior of these motifs in the same molecule. The RNA iFESs have single peaks, indicating that the combined motifs should denature as a single cohesive unit, rather than by regional melting. Local root-mean-square deviation (RMSD) analysis and communication propensity (CProp, variance in distances between residue pairs) reveal distinct motif properties. Our analysis indicates that the standard SRD is more stable than the viroid SRD, which is more stable than A-RNA. Base pairs at SRD to A-RNA transitions have limited flexibility. Application of CProp reveals extraordinary stiffness of the SRD, allowing residues on opposite sides of the motif to sense each other's motions.

CHARMM-GUI Enhanced Sampler for various collective variables and enhanced sampling methods

Enhanced sampling methodologies modifying underlying Hamiltonians can be used for the systems with a rugged potential energy surface that makes it hard to observe convergence using conventional unbiased molecular dynamics (MD) simulations. We present CHARMM-GUI Enhanced Sampler, a web-based tool to prepare various enhanced sampling simulations inputs with user-selected collective variables (CVs). Enhanced Sampler provides inputs for the following nine methods: accelerated MD, Gaussian accelerated MD, conformational flooding, metadynamics, adaptive biasing force, steered MD, temperature replica exchange MD, replica exchange solute tempering 2, and replica exchange umbrella sampling for the method-implemented MD packages including AMBER, CHARMM, GENESIS, GROMACS, NAMD, and OpenMM. Users only need to select a group of atoms via intuitive web-implementation in order to define commonly used nine CVs of interest: center of mass based distance, angle, dihedral, root-mean-square-distance, radius of gyration, distance projected on axis, two types of angles projected on axis, and coordination numbers. The enhanced sampling methods are tested with several biological systems to illustrate their efficiency over conventional MD. Enhanced Sampler with carefully optimized system-dependent parameters will help users to get meaningful results from their enhanced sampling simulations.

QM/MM and MM MD simulations on decontamination of the V-type nerve agent VX by phosphotriesterase: Toward a comprehensive understanding of steroselectivity and activity

Due to deadly toxicity and high environmental stability of the nerve agent VX, an efficient decontamination approach is desperately needed in tackling its severe threat to human secu-rity. The enzymatic...

FSATOOL 2.0: An integrated molecular dynamics simulation and trajectory data analysis program

Molecular dynamics simulation is important in the computational study of the biomolecules. In this paper, we upgrade our previous FSATOOL to version 2.0. It is no longer a plugin as before. Besides the existed enhanced sampling and Markov state model analysis module, FSATOOL 2.0 has three new features now. First, it contains a molecular dynamics simulation engine on both CPU and GPU device. The engine works with an embedded enhanced sampling module. Second, it can do the free energy calculation by various practical methods, including the weighted histogram analysis method and Gaussian mixture model. Third, it has many subroutines to process the trajectory data, such as principal component analysis, time-structure based independent component analysis, contact analysis, and Φ-value analysis. Most importantly, all these calculations are integrated into one package. The trajectory data format is compatible with all the modules. With a proper input parameter file, users can do the molecular dynamics simulation and data analysis work by only a few simplified commands. The capabilities and theoretical backgrounds of FSATOOL 2.0 are introduced in the paper.

Effects of H2A.B incorporation on nucleosome structures and dynamics

The H2A.B histone variant is an epigenetic regulator involved in transcriptional upregulation, DNA synthesis, and splicing that functions by replacing the canonical H2A histone in the nucleosome core particle. Introduction of H2A.B results in less compact nucleosome states with increased DNA unwinding and accessibility at the nucleosomal entry and exit sites. Despite being well characterized experimentally, the molecular mechanisms by which H2A.B incorporation alters nucleosome stability and dynamics remain poorly understood. To study the molecular mechanisms of H2A.B, we have performed a series of conventional and enhanced sampling molecular dynamics simulation of H2A.B- and canonical H2A-containing nucleosomes. Results of conventional simulations show that H2A.B weakens protein-protein and protein-DNA interactions at specific locations throughout the nucleosome. These weakened interactions result in significantly more DNA opening from both the entry and exit sites in enhanced sampling simulations. Furthermore, free energy profiles show that H2A.B-containing nucleosomes have significantly broader free wells and that H2A.B allows for sampling of states with increased DNA breathing, which are shown to be stable on the hundreds of nanoseconds timescale with further conventional simulations. Together, our results show the molecular mechanisms by which H2A.B creates less compacted nucleosome states as a means of increasing genetic accessibility and gene transcription.

Comparing Nonbonded Metal Ion Models in the Divalent Cation Binding Protein PsaA

Divalent metal cations are essential for many biological processes; however, accurately modeling divalent metal ions has proved a significant challenge for molecular dynamics force fields. Here we show that the choice of ion model influences the observed dynamics in PsaA, a metal binding protein from Streptococcus pneumoniae. We conduct extensive unbiased simulations and free energy calculations of PsaA bound to its cognate ligand Mn²⁺ and inhibitory ligand Zn²⁺ using three nonbonded ion models: a 12-6 model, a 12-6-4 model, and a multisite model. The observed coordination geometries and metal binding dynamics are sensitive to the choice of ion model, with the most dramatic differences observed in free energy calculations of ion release. We show that the conformational ensemble of Mn-bound PsaA is more similar to the crystallographic metal bound open state. This work extends the current model of PsaA metal binding and provides a framework for the rationalization of experimentally determined metal binding behavior. Our findings support the use of the 12-6-4 ion model for further simulations of divalent cation binding proteins.

Combining the biased and unbiased sampling strategy into one convenient free energy calculation method

Constructing a free energy landscape for a large molecule is difficult. One has to use either a high temperature or a strong driving force to enhance the sampling on the free energy barriers. In this work, we propose a mixed method that combines these two kinds of acceleration strategies into one simulation. First, it applies an adaptive biasing potential to some replicas of the molecule. These replicas are particularly accelerated in a collective variable space. Second, it places some unbiased and exchangeable replicas at various temperature levels. These replicas generate unbiased sampling data in the canonical ensemble. To improve the sampling efficiency, biased replicas transfer their state variables to the unbiased replicas after equilibrium by Monte Carlo trial moves. In comparison to previous integrated methods, it is more convenient for users. It does not need an initial reference biasing potential to guide the sampling of the molecule. And it is also unnecessary to insert many replicas for the requirement of passing the free energy barriers. The free energy calculation is accomplished in a single stage. It samples the data as fast as a biased simulation and it processes the data as simple as an unbiased simulation. The method provides a minimalist approach to the construction of the free energy landscape. © 2019 Wiley Periodicals, Inc.

Calculation of the Local Free Energy Landscape in the Restricted Region by the Modified Tomographic Method

The free energy landscape is the most important information in the study of the reaction mechanisms of the molecules. However, it is difficult to calculate. In a large collective variable space, a molecule must take a long time to obtain the sufficient sampling during the simulation. To save the calculation quantity, decreasing the sampling region and constructing the local free energy landscape is required in practice. However, the restricted region in the collective variable space may have an irregular shape. Simply restricting one or more collective variables of the molecule cannot satisfy the requirement. In this paper, we propose a modified tomographic method to perform the simulation. First, it divides the restricted region by some hyperplanes and connects the centers of hyperplanes together by a curve. Second, it forces the molecule to sample on the curve and the hyperplanes in the simulation and calculates the free energy data on them. Finally, all the free energy data are combined together to form the local free energy landscape. Without consideration of the area outside the restricted region, this free energy calculation can be more efficient. By this method, one can further optimize the path quickly in the collective variable space.