An octameric PqiC toroid stabilises the outer-membrane interaction of the PqiABC transport system.

The E. coli Paraquat Inducible (Pqi) Pathway is a putative Gram-negative phospholipid transport system. The pathway comprises three components: an integral inner membrane protein (PqiA), a periplasmic spanning MCE family protein (PqiB) and an outer membrane lipoprotein (PqiC). Interactions between all complex components, including stoichiometry, remain uncharacterised; nevertheless, once assembled into their quaternary complex, the trio of Pqi proteins are anticipated to provide a continuous channel between the inner and outer membranes of diderms. Here, we present X-ray structures of both the native and a truncated, soluble construct of the PqiC lipoprotein, providing insight into its biological assembly, and utilise neutron reflectometry to characterise the nature of the PqiB-PqiC-membrane interaction. Finally, we employ phenotypic complementation assays to probe specific PqiC residues, which imply the interaction between PqiB and PqiC is less intimate than previously anticipated.

py-MCMD: Python Software for Performing Hybrid Monte Carlo/Molecular Dynamics Simulations with GOMC and NAMD.

py-MCMD, an open-source Python software, provides a robust workflow layer that manages communication of relevant system information between the simulation engines NAMD and GOMC and generates coherent thermodynamic properties and trajectories for analysis. To validate the workflow and highlight its capabilities, hybrid Monte Carlo/molecular dynamics (MC/MD) simulations are performed for SPC/E water in the isobaric-isothermal (NPT) and grand canonical (GC) ensembles as well as with Gibbs ensemble Monte Carlo (GEMC). The hybrid MC/MD approach shows close agreement with reference MC simulations and has a computational efficiency that is 2 to 136 times greater than traditional Monte Carlo simulations. MC/MD simulations performed for water in a graphene slit pore illustrate significant gains in sampling efficiency when the coupled-decoupled configurational-bias MC (CD-CBMC) algorithm is used compared with simulations using a single unbiased random trial position. Simulations using CD-CBMC reach equilibrium with 25 times fewer cycles than simulations using a single unbiased random trial position, with a small increase in computational cost. In a more challenging application, hybrid grand canonical Monte Carlo/molecular dynamics (GCMC/MD) simulations are used to hydrate a buried binding pocket in bovine pancreatic trypsin inhibitor. Water occupancies produced by GCMC/MD simulations are in close agreement with crystallographically identified positions, and GCMC/MD simulations have a computational efficiency that is 5 times better than MD simulations. py-MCMD is available on GitHub at https://github.com/GOMC-WSU/py-MCMD.

Experiences Porting NAMD to the Data Parallel C++ Programming Model.

HPC applications have a growing need to leverage heterogeneous computing resources with a vendor-neutral programming paradigm. Data Parallel C++ is a programming language based on open standards SYCL, providing a vendor-neutral solution. We describe our experiences porting the NAMD molecular dynamics application with its GPU-offload force kernels to SYCL/DPC++. Results are shown that demonstrate correctness of the porting effort.

Intelligent resolution: Integrating Cryo-EM with AI-driven multi-resolution simulations to observe the severe acute respiratory syndrome coronavirus-2 replication-transcription machinery in action.

The severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) replication transcription complex (RTC) is a multi-domain protein responsible for replicating and transcribing the viral mRNA inside a human cell. Attacking RTC function with pharmaceutical compounds is a pathway to treating COVID-19. Conventional tools, e.g., cryo-electron microscopy and all-atom molecular dynamics (AAMD), do not provide sufficiently high resolution or timescale to capture important dynamics of this molecular machine. Consequently, we develop an innovative workflow that bridges the gap between these resolutions, using mesoscale fluctuating finite element analysis (FFEA) continuum simulations and a hierarchy of AI-methods that continually learn and infer features for maintaining consistency between AAMD and FFEA simulations. We leverage a multi-site distributed workflow manager to orchestrate AI, FFEA, and AAMD jobs, providing optimal resource utilization across HPC centers. Our study provides unprecedented access to study the SARS-CoV-2 RTC machinery, while providing general capability for AI-enabled multi-resolution simulations at scale.

Mental Workload in Neuropsychology: An Example With the NASA-TLX in Adults With HIV.

A preliminary set of analyses are presented, where workload was examined in 32 adults infected with the human immunodeficiency virus (HIV). Like the current COVID-19 pandemic (caused by the SARS-CoV-2 virus), HIV can produce a wide variety of symptoms, including various levels of cognitive dysfunction. In fact, a recent meta-analysis estimates that of the 39 million adults infected globally with HIV, 42.6% exhibit some form of HIV-associated neurocognitive disorder. A common cognitive symptom in HIV is decline in attention and executive functioning. Though typically examined by clinicians with less precise traditional paper-and-pencil neuropsychological tests, we examined this aspect of cognitive functioning using a more psychometrically sophisticated task as we had HIV-positive adults perform a computerized tracking task in single, dual, and tri-task conditions via the Multi-Attribute Task (MAT) Battery. Also assessed was mental workload, with the NASA-Task Load Index (NASA-TLX), rarely used in neuropsychology but a standard tool in human factors and neuroergonomics research. As expected, tracking performance declined with task condition difficulty (p < 0.001). Although no direct statistical comparisons were made, MAT performance here appeared worse than the MAT performance of various other groups reported in the research literature and in our laboratory. Ratings of workload also tended to increase as a function of task condition difficulty (p < 0.001). Plotting MAT tracking performance against the Mental Demand subscale scores, large individual differences in this aspect of workload were evident in both optimal and sub-optimal tracking performance. To examine likely variables with a potential impact on Mental Demand, a variety of variables (nadir CD4 count, viral load, depression symptoms, diagnosis of AIDS, presence of opportunistic infection, general cognitive status, etc.) were examined in relation to the Mental Demand scale, with age showing a significant association (r = 0.41, p = 0.022) and a diagnosis of AIDS showing trend associations (ps ≥ 0.066). Findings suggesting a deficit in metacognition or insight are also discussed. It is argued that assessment of workload (and its various aspects or components) can provide valuable additional information in neuropsychology.

Surface-tethered planar membranes containing the ß-barrel assembly machinery: a platform for investigating bacterial outer membrane protein folding.

The outer membrane of Gram-negative bacteria presents a robust physicochemical barrier protecting the cell from both the natural environment and acting as the first line of defense against antimicrobial materials. The proteins situated within the outer membrane are responsible for a range of biological functions including controlling influx and efflux. These outer membrane proteins (OMPs) are ultimately inserted and folded within the membrane by the ß-barrel assembly machine (Bam) complex. The precise mechanism by which the Bam complex folds and inserts OMPs remains unclear. Here, we have developed a platform for investigating Bam-mediated OMP insertion. By derivatizing a gold surface with a copper-chelating self-assembled monolayer, we were able to assemble a planar system containing the complete Bam complex reconstituted within a phospholipid bilayer. Structural characterization of this interfacial protein-tethered bilayer by polarized neutron reflectometry revealed distinct regions consistent with known high-resolution models of the Bam complex. Additionally, by monitoring changes of mass associated with OMP insertion by quartz crystal microbalance with dissipation monitoring, we were able to demonstrate the functionality of this system by inserting two diverse OMPs within the membrane, pertactin, and OmpT. This platform has promising application in investigating the mechanism of Bam-mediated OMP insertion, in addition to OMP function and activity within a phospholipid bilayer environment.

Neuroergonomics: A Perspective from Neuropsychology, with a Proposal about Workload.

In a brief overview of neuroergonomics, including some personal reminiscences of Raja Parasuraman, it is recognized that the field of human factors and ergonomics has benefitted greatly from the inclusion and integration of neuroscientific methods and theory. It is argued that such synergistic success can work in the other direction as well with the inclusion of methods and theory of human factors by a neuro field, in this case, neuropsychology. More specifically, it is proposed that neuropsychology can benefit from the inclusion of workload measures and theory. Preliminary studies on older adults, persons living with HIV, and patients with a traumatic brain injury or multiple sclerosis, are reviewed. As an adjunct measure to neuropsychological tests, the construct of workload seems perfectly suited to provide an additional vector of information on patient status, capturing some of the large individual differences evident in clinical populations and facilitating the early detection of cognitive change.

Multilevel summation for periodic electrostatics using B-splines.

Fast methods for calculating two-body interactions have many applications, and for molecular science and cosmology, it is common to employ periodic boundary conditions. However, for the 1/r potential, the energy and forces are ill-defined. Adopted here is the model given by the classic Ewald sum. For the fast calculation of two-body forces, the most celebrated method is the fast multipole method and its tree-code predecessor. However, molecular simulations typically employ mesh-based approximations and the fast Fourier transform. Both types of methods have significant drawbacks, which, in most respects, are overcome by the less well-known multilevel summation method (MSM). Presented here is a realization of the MSM, which can be regarded as a multilevel extension of the (smoothed) particle mesh Ewald (PME) method, but with the Ewald softening replaced by one having a finite range. The two-level (single-grid) version of MSM requires fewer tuning parameters than PME and is marginally faster. Additionally, higher-level versions of MSM scale well to large numbers of processors, whereas PME and other two-level methods do not. Although higher-level versions of MSM are less efficient on a single processor than the two-level version, evidence suggests that they are more efficient than other methods that scale well, such as the fast multipole method and tree codes.

Lessons Learned from Responsive Molecular Dynamics Studies of the COVID-19 Virus.

Over the past 18 months, the need to perform atomic detail molecular dynamics simulations of the SARS-CoV-2 virion, its spike protein, and other structures related to the viral infection cycle has led biomedical researchers worldwide to urgently seek out all available biomolecular structure information, appropriate molecular modeling and simulation software, and the necessary computing resources to conduct their work. We describe our experiences from several COVID-19 research collaborations and the challenges they presented in terms of our molecular modeling software development and support efforts, our laboratory's local computing environment, and our scientists' use of non-traditional HPC hardware platforms such as public clouds for large scale parallel molecular dynamics simulations.

Incidental Learning and Memory Deficits on a Computerized Symbol-Digit Modalities Test in Adults with HIV/AIDS.

OBJECTIVE: Incidental learning and memory, as well as processing speed, were examined in human immunodeficiency virus (HIV)-positive adults and a seronegative control group. METHODS: Participants completed a computerized Symbol-Digit Modalities Test (cSDMT) with two blocked conditions: a set of trials with the standard symbol-digit pairings and the second set with a rearranged symbol-digit pairings. RESULTS: HIV-positive adults showed slower overall reaction time compared to the HIV-negative group. More importantly, the most cognitively impaired HIV-positive group showed no interference in the rearranged set of symbol-digit pairings from the standard pairings on the cSDMT. CONCLUSION: The relative slowing, or interference, in the HIV-negative group and two HIV-positive groups (unimpaired and impaired) was quite large (between 122 and 131 ms). We argue that the lack of such relative slowing in the most cognitively impaired HIV-positive group indicates a deficit in incidental learning and memory.

AI-driven multiscale simulations illuminate mechanisms of SARS-CoV-2 spike dynamics.

We develop a generalizable AI-driven workflow that leverages heterogeneous HPC resources to explore the time-dependent dynamics of molecular systems. We use this workflow to investigate the mechanisms of infectivity of the SARS-CoV-2 spike protein, the main viral infection machinery. Our workflow enables more efficient investigation of spike dynamics in a variety of complex environments, including within a complete SARS-CoV-2 viral envelope simulation, which contains 305 million atoms and shows strong scaling on ORNL Summit using NAMD. We present several novel scientific discoveries, including the elucidation of the spike's full glycan shield, the role of spike glycans in modulating the infectivity of the virus, and the characterization of the flexible interactions between the spike and the human ACE2 receptor. We also demonstrate how AI can accelerate conformational sampling across different systems and pave the way for the future application of such methods to additional studies in SARS-CoV-2 and other molecular systems.

AI-Driven Multiscale Simulations Illuminate Mechanisms of SARS-CoV-2 Spike Dynamics.

We develop a generalizable AI-driven workflow that leverages heterogeneous HPC resources to explore the time-dependent dynamics of molecular systems. We use this workflow to investigate the mechanisms of infectivity of the SARS-CoV-2 spike protein, the main viral infection machinery. Our workflow enables more efficient investigation of spike dynamics in a variety of complex environments, including within a complete SARS-CoV-2 viral envelope simulation, which contains 305 million atoms and shows strong scaling on ORNL Summit using NAMD. We present several novel scientific discoveries, including the elucidation of the spike's full glycan shield, the role of spike glycans in modulating the infectivity of the virus, and the characterization of the flexible interactions between the spike and the human ACE2 receptor. We also demonstrate how AI can accelerate conformational sampling across different systems and pave the way for the future application of such methods to additional studies in SARS-CoV-2 and other molecular systems.

Memory in repeat sports-related concussive injury and single-impact traumatic brain injury.

Background: Repeat sports-related concussive/subconcussive injury (RC/SCI) is related to memory impairment. Objective & Methods: We sought to determine memory differences between persons with RC/SCI, moderate-to-severe single-impact traumatic brain injury (SI-TBI), and healthy controls. MRI scans from a subsample of participants with SI-TBI were used to identify the neuroanatomical correlates of observed memory process differences between the brain injury groups. Results: Both brain injury groups evidenced worse learning and recall in contrast to controls, although SI-TBI group had poorer memory than the RC/SCI group. Regarding memory process differences, in contrast to controls, the SI-TBI group evidenced difficulties with encoding, consolidation, and retrieval, while the RC/SCI group showed deficits in consolidation and retrieval. Delayed recall was predicted by encoding, with consolidation as a secondary predictor in the SI-TBI group. In the RC/SCI group, delayed recall was only predicted by consolidation. MRI data showed that the consolidation index we used mapped onto hippocampal atrophy. Conclusions: RC/SCI is primarily associated with consolidation deficits, which differs from SI-TBI. Given the role of the hippocampus in memory consolidation and the fact that hyperphosphorylated tau tends to accumulate in the medial temporal lobe in RC/SCI, consolidation deficits may be a cognitive marker of chronic traumatic encephalopathy in athletes.

Scalable molecular dynamics on CPU and GPU architectures with NAMD.

NAMDis a molecular dynamics program designed for high-performance simulations of very large biological objects on CPU- and GPU-based architectures. NAMD offers scalable performance on petascale parallel supercomputers consisting of hundreds of thousands of cores, as well as on inexpensive commodity clusters commonly found in academic environments. It is written in C++ and leans on Charm++ parallel objects for optimal performance on low-latency architectures. NAMD is a versatile, multipurpose code that gathers state-of-the-art algorithms to carry out simulations in apt thermodynamic ensembles, using the widely popular CHARMM, AMBER, OPLS, and GROMOS biomolecular force fields. Here, we review the main features of NAMD that allow both equilibrium and enhanced-sampling molecular dynamics simulations with numerical efficiency. We describe the underlying concepts utilized by NAMD and their implementation, most notably for handling long-range electrostatics; controlling the temperature, pressure, and pH; applying external potentials on tailored grids; leveraging massively parallel resources in multiple-copy simulations; and hybrid quantum-mechanical/molecular-mechanical descriptions. We detail the variety of options offered by NAMD for enhanced-sampling simulations aimed at determining free-energy differences of either alchemical or geometrical transformations and outline their applicability to specific problems. Last, we discuss the roadmap for the development of NAMD and our current efforts toward achieving optimal performance on GPU-based architectures, for pushing back the limitations that have prevented biologically realistic billion-atom objects to be fruitfully simulated, and for making large-scale simulations less expensive and easier to set up, run, and analyze. NAMD is distributed free of charge with its source code at www.ks.uiuc.edu.

Boosting Free-Energy Perturbation Calculations with GPU-Accelerated NAMD.

Harnessing the power of graphics processing units (GPUs) to accelerate molecular dynamics (MD) simulations in the context of free-energy calculations has been a longstanding effort toward the development of versatile, high-performance MD engines. We report a new GPU-based implementation in NAMD of free-energy perturbation (FEP), one of the oldest, most popular importance-sampling approaches for the determination of free-energy differences that underlie alchemical transformations. Compared to the CPU implementation available since 2001 in NAMD, our benchmarks indicate that the new implementation of FEP in traditional GPU code is about four times faster, without any noticeable loss of accuracy, thereby paving the way toward more affordable free-energy calculations on large biological objects. Moreover, we have extended this new FEP implementation to a code path highly optimized for a single-GPU node, which proves to be up to nearly 30 times faster than the CPU implementation. Through optimized GPU performance, the present developments provide the community with a cost-effective solution for conducting FEP calculations. The new FEP-enabled code has been released with NAMD 3.0.

Assessing workload in neuropsychology: An illustration with the Tower of Hanoi test.

Workload is a common and useful construct in human factors research that has been largely overlooked in other areas of psychology, including neuropsychology, where it could be effectively employed both theoretically and practically. A popular subjective measure of workload, the NASA-Task Load Index (NASA-TLX), is illustrated with a computerized version of the Tower of Hanoi (TOH), a typical neuropsychological test of executive function. Reported workload, especially as an overall measure and also for the Mental Demand and Effort subscales, was greater in the more difficult TOH conditions and was positively correlated with number of moves to complete the TOH as well as completion time. Thus, results support the utility or construct validity of the NASA-TLX in reflecting workload states in the individual as well as various demands of the neuropsychological test (the timing, physical demands, etc.). It is argued that workload can be a useful construct in neuropsychological assessment, providing an additional channel of information on patient status. For instance, what does it mean if test performance for a patient is at a typical level (indicating no deficit) but workload is exceptionally high?

Diagnostic utility of the HIV dementia scale and the international HIV dementia scale in screening for HIV-associated neurocognitive disorders among Spanish-speaking adults.

Given that neurocognitive impairment is a frequent complication of HIV-1 infection in Spanish-speaking adults, the limited number of studies assessing HIV-associated neurocognitive disorders (HAND) in this population raises serious clinical concern. In addition to being appropriately translated, instruments need to be modified, normed, and validated accordingly. The purpose of the current study was to examine the diagnostic utility of the HIV Dementia Scale (HDS) and International HIV Dementia Scale (IHDS) to screen for HAND in Spanish-speaking adults living with HIV infection. Participants were classified as either HAND (N = 47) or No-HAND (N = 53) after completing a comprehensive neuropsychological evaluation. Receiver operating characteristic analyses found the HDS (AUC = .706) was more sensitive to detecting HAND than the IHDS (AUC = .600). Optimal cutoff scores were 9.5 for the HDS (PPV = 65.2%, NPV = 71.4%) and 9.0 for the IHDS (PPV = 59.4%, NPV = 59.1%). Canonical Correlation Analysis found the HDS converged with attention and executive functioning. Findings suggest that while the IHDS may not be an appropriate screening instrument with this population, the HDS retains sufficient statistical validity and clinical utility to screen for HAND in Spanish-speaking adults as a time-efficient and cost-effective measure in clinical settings with limited resources.

Membrane protein extraction and purification using styrene-maleic acid (SMA) copolymer: effect of variations in polymer structure.

The use of styrene-maleic acid (SMA) copolymers to extract and purify transmembrane proteins, while retaining their native bilayer environment, overcomes many of the disadvantages associated with conventional detergent-based procedures. This approach has huge potential for the future of membrane protein structural and functional studies. In this investigation, we have systematically tested a range of commercially available SMA polymers, varying in both the ratio of styrene and maleic acid and in total size, for the ability to extract, purify and stabilise transmembrane proteins. Three different membrane proteins (BmrA, LeuT and ZipA), which vary in size and shape, were used. Our results show that several polymers, can be used to extract membrane proteins, comparably to conventional detergents. A styrene:maleic acid ratio of either 2:1 or 3:1, combined with a relatively small average molecular mass (7.5-10 kDa), is optimal for membrane extraction, and this appears to be independent of the protein size, shape or expression system. A subset of polymers were taken forward for purification, functional and stability tests. Following a one-step affinity purification, SMA 2000 was found to be the best choice for yield, purity and function. However, the other polymers offer subtle differences in size and sensitivity to divalent cations that may be useful for a variety of downstream applications.

TopoGromacs: Automated Topology Conversion from CHARMM to GROMACS within VMD.

Molecular dynamics (MD) simulation engines use a variety of different approaches for modeling molecular systems with force fields that govern their dynamics and describe their topology. These different approaches introduce incompatibilities between engines, and previously published software bridges the gaps between many popular MD packages, such as between CHARMM and AMBER or GROMACS and LAMMPS. While there are many structure building tools available that generate topologies and structures in CHARMM format, only recently have mechanisms been developed to convert their results into GROMACS input. We present an approach to convert CHARMM-formatted topology and parameters into a format suitable for simulation with GROMACS by expanding the functionality of TopoTools, a plugin integrated within the widely used molecular visualization and analysis software VMD. The conversion process was diligently tested on a comprehensive set of biological molecules in vacuo. The resulting comparison between energy terms shows that the translation performed was lossless as the energies were unchanged for identical starting configurations. By applying the conversion process to conventional benchmark systems that mimic typical modestly sized MD systems, we explore the effect of the implementation choices made in CHARMM, NAMD, and GROMACS. The newly available automatic conversion capability breaks down barriers between simulation tools and user communities and allows users to easily compare simulation programs and leverage their unique features without the tedium of constructing a topology twice.

Multilevel summation with B-spline interpolation for pairwise interactions in molecular dynamics simulations.

The multilevel summation method for calculating electrostatic interactions in molecular dynamics simulations constructs an approximation to a pairwise interaction kernel and its gradient, which can be evaluated at a cost that scales linearly with the number of atoms. The method smoothly splits the kernel into a sum of partial kernels of increasing range and decreasing variability with the longer-range parts interpolated from grids of increasing coarseness. Multilevel summation is especially appropriate in the context of dynamics and minimization, because it can produce continuous gradients. This article explores the use of B-splines to increase the accuracy of the multilevel summation method (for nonperiodic boundaries) without incurring additional computation other than a preprocessing step (whose cost also scales linearly). To obtain accurate results efficiently involves technical difficulties, which are overcome by a novel preprocessing algorithm. Numerical experiments demonstrate that the resulting method offers substantial improvements in accuracy and that its performance is competitive with an implementation of the fast multipole method in general and markedly better for Hamiltonian formulations of molecular dynamics. The improvement is great enough to establish multilevel summation as a serious contender for calculating pairwise interactions in molecular dynamics simulations. In particular, the method appears to be uniquely capable for molecular dynamics in two situations, nonperiodic boundary conditions and massively parallel computation, where the fast Fourier transform employed in the particle-mesh Ewald method falls short.