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GROMACS is a widely-used molecular dynamics software package with a focus on performance, portability, and maintainability across a broad range of platforms. Thanks to its early algorithmic redesign and flexible heterogeneous parallelization, GROMACS has successfully harnessed GPU accelerators for more than a decade.With the diversification of accelerator platforms in HPC and no obvious choice for a well-suited multi-vendor programming model, the GROMACS project found itself at a crossroads. The performance and portability requirements, as well as a strong preference for a standards-based programming model, motivated our choice to use SYCL for production on both new HPC GPU platforms: AMD and Intel.Since the GROMACS 2022 release, the SYCL backend has been the primary means to target AMD GPUs in preparation for exascale HPC architectures like LUMI and Frontier.SYCL is a cross-platform, royalty-free, C++17-based standard for programming hardware accelerators, from embedded to HPC.It allows using the same code to target GPUs from all three major vendors with minimal specialization, which offers major portability benefits.While SYCL implementations build on native compilers and runtimes, whether such an approach is performant is not immediately evident.Biomolecular simulations have challenging performance characteristics: latency sensitivity, the need for strong scaling, and typical iteration times as short as hundreds of microseconds. Hence, obtaining good performance across the range of problem sizes and scaling regimes is particularly challenging.Here, we share the results of our work on readying GROMACS for AMD GPU platforms using SYCL,and demonstrate performance on Cray EX235a machines with MI250X accelerators. Our findings illustrate that portability is possible without major performance compromises.We provide a detailed analysis of node-level kernel and runtime performance with the aim of sharing best practices with the HPC community on using SYCL as a performanc, qc 20240802

GROMACS is a widely-used molecular dynamics software package with a focus on performance, portability, and maintainability across a broad range of platforms. Thanks to its early algorithmic redesign and flexible heterogeneous parallelization, GROMACS has successfully harnessed GPU accelerators for more than a decade.With the diversification of accelerator platforms in HPC and no obvious choice for a well-suited multi-vendor programming model, the GROMACS project found itself at a crossroads. The performance and portability requirements, as well as a strong preference for a standards-based programming model, motivated our choice to use SYCL for production on both new HPC GPU platforms: AMD and Intel.Since the GROMACS 2022 release, the SYCL backend has been the primary means to target AMD GPUs in preparation for exascale HPC architectures like LUMI and Frontier.SYCL is a cross-platform, royalty-free, C++17-based standard for programming hardware accelerators, from embedded to HPC.It allows using the same code to target GPUs from all three major vendors with minimal specialization, which offers major portability benefits.While SYCL implementations build on native compilers and runtimes, whether such an approach is performant is not immediately evident.Biomolecular simulations have challenging performance characteristics: latency sensitivity, the need for strong scaling, and typical iteration times as short as hundreds of microseconds. Hence, obtaining good performance across the range of problem sizes and scaling regimes is particularly challenging.Here, we share the results of our work on readying GROMACS for AMD GPU platforms using SYCL,and demonstrate performance on Cray EX235a machines with MI250X accelerators. Our findings illustrate that portability is possible without major performance compromises.We provide a detailed analysis of node-level kernel and runtime performance with the aim of sharing best practices with the HPC community on using SYCL as a performanc, qc 20240802

GROMACS is a widely-used molecular dynamics software package with a focus on performance, portability, and maintainability across a broad range of platforms. Thanks to its early algorithmic redesign and flexible heterogeneous parallelization, GROMACS has successfully harnessed GPU accelerators for more than a decade.With the diversification of accelerator platforms in HPC and no obvious choice for a well-suited multi-vendor programming model, the GROMACS project found itself at a crossroads. The performance and portability requirements, as well as a strong preference for a standards-based programming model, motivated our choice to use SYCL for production on both new HPC GPU platforms: AMD and Intel.Since the GROMACS 2022 release, the SYCL backend has been the primary means to target AMD GPUs in preparation for exascale HPC architectures like LUMI and Frontier.SYCL is a cross-platform, royalty-free, C++17-based standard for programming hardware accelerators, from embedded to HPC.It allows using the same code to target GPUs from all three major vendors with minimal specialization, which offers major portability benefits.While SYCL implementations build on native compilers and runtimes, whether such an approach is performant is not immediately evident.Biomolecular simulations have challenging performance characteristics: latency sensitivity, the need for strong scaling, and typical iteration times as short as hundreds of microseconds. Hence, obtaining good performance across the range of problem sizes and scaling regimes is particularly challenging.Here, we share the results of our work on readying GROMACS for AMD GPU platforms using SYCL,and demonstrate performance on Cray EX235a machines with MI250X accelerators. Our findings illustrate that portability is possible without major performance compromises.We provide a detailed analysis of node-level kernel and runtime performance with the aim of sharing best practices with the HPC community on using SYCL as a performanc, qc 20240802

The COVID-19 pandemic demonstrates that a top priority for society, now and in the future, is to be able to respond quickly to diseases with effective treatments. Among the new tools that pharmaceutical industries and researchers have in their hands nowadays, there are the extensive computer simulations capable of evaluating in-silico the interaction between possible drugs and the target proteins. The central goal of the LIGATE project is to create and validate a leading application solution for drug discovery in High-Performance Computing (HPC) systems up to the exascale level. The overall project purpose is the automation of the drug design process, which is currently performed with substantial human effort throughout the different phases of the process: preparation of input parameters, management of data sets with billions of molecules, interaction with HPC queue management systems to handle jobs, and optimization of scoring function parameters and thresholds., QC 20240822

Loss-of-function mutations of the CFTR gene cause the life-shortening genetic disease cystic fibrosis (CF), whereas overactivity of CFTR may lead to secretory diarrhea and polycystic kidney disease. While effective drugs targeting the CFTR protein have been developed for the treatment of CF, little progress has been made for diseases caused by hyper-activated CFTR. Here, we solve the cryo-EM structure of CFTR in complex with CFTRinh-172 (Inh-172), a CFTR gating inhibitor with promising potency and efficacy. We find that Inh-172 binds inside the pore of CFTR, interacting with amino acid residues from transmembrane segments (TMs) 1, 6, 8, 9, and 12 through mostly hydrophobic interactions and a salt bridge. Substitution of these residues lowers the apparent affinity of Inh-172. The inhibitor-bound structure reveals re-orientations of the extracellular segment of TMs 1, 8, and 12, supporting an allosteric modulation mechanism involving post-binding conformational changes. This allosteric inhibitory mechanism readily explains our observations that pig CFTR, which preserves all the amino acid residues involved in Inh-172 binding, exhibits a much-reduced sensitivity to Inh-172 and that the apparent affinity of Inh-172 is altered by the CF drug ivacaftor (i.e., VX-770) which enhances CFTR’s activity through binding to a site also comprising TM8., QC 20240830

GROMACS is a widely-used molecular dynamics software package with a focus on performance, portability, and maintainability across a broad range of platforms. Thanks to its early algorithmic redesign and flexible heterogeneous parallelization, GROMACS has successfully harnessed GPU accelerators for more than a decade.With the diversification of accelerator platforms in HPC and no obvious choice for a well-suited multi-vendor programming model, the GROMACS project found itself at a crossroads. The performance and portability requirements, as well as a strong preference for a standards-based programming model, motivated our choice to use SYCL for production on both new HPC GPU platforms: AMD and Intel.Since the GROMACS 2022 release, the SYCL backend has been the primary means to target AMD GPUs in preparation for exascale HPC architectures like LUMI and Frontier.SYCL is a cross-platform, royalty-free, C++17-based standard for programming hardware accelerators, from embedded to HPC.It allows using the same code to target GPUs from all three major vendors with minimal specialization, which offers major portability benefits.While SYCL implementations build on native compilers and runtimes, whether such an approach is performant is not immediately evident.Biomolecular simulations have challenging performance characteristics: latency sensitivity, the need for strong scaling, and typical iteration times as short as hundreds of microseconds. Hence, obtaining good performance across the range of problem sizes and scaling regimes is particularly challenging.Here, we share the results of our work on readying GROMACS for AMD GPU platforms using SYCL,and demonstrate performance on Cray EX235a machines with MI250X accelerators. Our findings illustrate that portability is possible without major performance compromises.We provide a detailed analysis of node-level kernel and runtime performance with the aim of sharing best practices with the HPC community on using SYCL as a performanc, qc 20240802

Glycine receptors are pentameric ligand-gated ion channels that conduct chloride ions across postsynaptic membranes to facilitate fast inhibitory neurotransmission. In addition to gating by the glycine agonist, interactions with lipids and other compounds in the surrounding membrane environment modulate their function, but molecular details of these interactions remain unclear, in particular, for cholesterol. Here, we report coarse-grained simulations in a model neuronal membrane for three zebrafish glycine receptor structures representing apparent resting, open, and desensitized states. We then converted the systems to all-atom models to examine detailed lipid interactions. Cholesterol bound to the receptor at an outer-leaflet intersubunit site, with a preference for the open and desensitized versus resting states, indicating that it can bias receptor function. Finally, we used short atomistic simulations and iterative amino acid perturbations to identify residues that may mediate allosteric gating transitions. Frequent cholesterol contacts in atomistic simulations clustered with residues identified by perturbation analysis and overlapped with mutations influencing channel function and pathology. Cholesterol binding at this site was also observed in a recently reported pig heteromeric glycine receptor. These results indicate state-dependent lipid interactions relevant to allosteric transitions of glycine receptors, including specific amino acid contacts applicable to biophysical modeling and pharmaceutical design., QC 20240603

GROMACS is a widely-used molecular dynamics software package with a focus on performance, portability, and maintainability across a broad range of platforms. Thanks to its early algorithmic redesign and flexible heterogeneous parallelization, GROMACS has successfully harnessed GPU accelerators for more than a decade.With the diversification of accelerator platforms in HPC and no obvious choice for a well-suited multi-vendor programming model, the GROMACS project found itself at a crossroads. The performance and portability requirements, as well as a strong preference for a standards-based programming model, motivated our choice to use SYCL for production on both new HPC GPU platforms: AMD and Intel.Since the GROMACS 2022 release, the SYCL backend has been the primary means to target AMD GPUs in preparation for exascale HPC architectures like LUMI and Frontier.SYCL is a cross-platform, royalty-free, C++17-based standard for programming hardware accelerators, from embedded to HPC.It allows using the same code to target GPUs from all three major vendors with minimal specialization, which offers major portability benefits.While SYCL implementations build on native compilers and runtimes, whether such an approach is performant is not immediately evident.Biomolecular simulations have challenging performance characteristics: latency sensitivity, the need for strong scaling, and typical iteration times as short as hundreds of microseconds. Hence, obtaining good performance across the range of problem sizes and scaling regimes is particularly challenging.Here, we share the results of our work on readying GROMACS for AMD GPU platforms using SYCL,and demonstrate performance on Cray EX235a machines with MI250X accelerators. Our findings illustrate that portability is possible without major performance compromises.We provide a detailed analysis of node-level kernel and runtime performance with the aim of sharing best practices with the HPC community on using SYCL as a performanc, qc 20240802

Ligand-gated ion channels transduce electrochemical signals in neurons and other excitable cells. Aside fromcanonical ligands, phospholipids are thought to bind specifically to the transmembrane domain of several ionchannels. However, structural details of such lipid contacts remain elusive, partly due to limited resolution ofthese regions in experimental structures. Here, we discovered multiple lipid interactions in the channel GLICby integrating cryo-electron microscopy and large-scale molecular simulations. We identified 25 bound lipidsin the GLIC closed state, a conformation where none, to our knowledge, were previously known. Three lipidswere associated with each subunit in the inner leaflet, including a buried interaction disrupted in mutantsimulations. In the outer leaflet, two intrasubunit sites were evident in both closed and open states, whilea putative intersubunit site was preferred in open-state simulations. This work offers molecular details ofGLIC-lipid contacts particularly in the ill-characterized closed state, testable hypotheses for state-dependentbinding, and a multidisciplinary strategy for modeling protein-lipid interactions., QC 20230522

Ligand-gated ion channels transduce electrochemical signals in neurons and other excitable cells. Aside fromcanonical ligands, phospholipids are thought to bind specifically to the transmembrane domain of several ionchannels. However, structural details of such lipid contacts remain elusive, partly due to limited resolution ofthese regions in experimental structures. Here, we discovered multiple lipid interactions in the channel GLICby integrating cryo-electron microscopy and large-scale molecular simulations. We identified 25 bound lipidsin the GLIC closed state, a conformation where none, to our knowledge, were previously known. Three lipidswere associated with each subunit in the inner leaflet, including a buried interaction disrupted in mutantsimulations. In the outer leaflet, two intrasubunit sites were evident in both closed and open states, whilea putative intersubunit site was preferred in open-state simulations. This work offers molecular details ofGLIC-lipid contacts particularly in the ill-characterized closed state, testable hypotheses for state-dependentbinding, and a multidisciplinary strategy for modeling protein-lipid interactions., QC 20230522

Ligand-gated ion channels transduce electrochemical signals in neurons and other excitable cells. Aside fromcanonical ligands, phospholipids are thought to bind specifically to the transmembrane domain of several ionchannels. However, structural details of such lipid contacts remain elusive, partly due to limited resolution ofthese regions in experimental structures. Here, we discovered multiple lipid interactions in the channel GLICby integrating cryo-electron microscopy and large-scale molecular simulations. We identified 25 bound lipidsin the GLIC closed state, a conformation where none, to our knowledge, were previously known. Three lipidswere associated with each subunit in the inner leaflet, including a buried interaction disrupted in mutantsimulations. In the outer leaflet, two intrasubunit sites were evident in both closed and open states, whilea putative intersubunit site was preferred in open-state simulations. This work offers molecular details ofGLIC-lipid contacts particularly in the ill-characterized closed state, testable hypotheses for state-dependentbinding, and a multidisciplinary strategy for modeling protein-lipid interactions., QC 20230522

Ligand-gated ion channels transduce electrochemical signals in neurons and other excitable cells. Aside fromcanonical ligands, phospholipids are thought to bind specifically to the transmembrane domain of several ionchannels. However, structural details of such lipid contacts remain elusive, partly due to limited resolution ofthese regions in experimental structures. Here, we discovered multiple lipid interactions in the channel GLICby integrating cryo-electron microscopy and large-scale molecular simulations. We identified 25 bound lipidsin the GLIC closed state, a conformation where none, to our knowledge, were previously known. Three lipidswere associated with each subunit in the inner leaflet, including a buried interaction disrupted in mutantsimulations. In the outer leaflet, two intrasubunit sites were evident in both closed and open states, whilea putative intersubunit site was preferred in open-state simulations. This work offers molecular details ofGLIC-lipid contacts particularly in the ill-characterized closed state, testable hypotheses for state-dependentbinding, and a multidisciplinary strategy for modeling protein-lipid interactions., QC 20230522

Ligand-gated ion channels transduce electrochemical signals in neurons and other excitable cells. Aside fromcanonical ligands, phospholipids are thought to bind specifically to the transmembrane domain of several ionchannels. However, structural details of such lipid contacts remain elusive, partly due to limited resolution ofthese regions in experimental structures. Here, we discovered multiple lipid interactions in the channel GLICby integrating cryo-electron microscopy and large-scale molecular simulations. We identified 25 bound lipidsin the GLIC closed state, a conformation where none, to our knowledge, were previously known. Three lipidswere associated with each subunit in the inner leaflet, including a buried interaction disrupted in mutantsimulations. In the outer leaflet, two intrasubunit sites were evident in both closed and open states, whilea putative intersubunit site was preferred in open-state simulations. This work offers molecular details ofGLIC-lipid contacts particularly in the ill-characterized closed state, testable hypotheses for state-dependentbinding, and a multidisciplinary strategy for modeling protein-lipid interactions., QC 20230522

Isocitrate dehydrogenase 2 (IDH2) is a homodimeric enzyme that plays an important role in energy production. A mutation R140Q in one monomer makes the enzyme tumourigenic. Enasidenib is an effective inhibitor of IDH2/R140Q. A secondary mutation Q316E leads to enasidenib resistance. This mutation was hitherto only found in trans, i.e. where one monomer has the R140Q mutation and the other carries the Q316E mutation. It is not clear if the mutation only leads to resistance when in trans or if it has been discovered in {\em trans} only by chance, since it was only reported in two patients. Using molecular dynamics (MD) simulations we show that the binding of enasidenib to IDH2 is indeed much weaker when the Q316E mutation takes place in trans not in cis, which provides a molecular explanation for the clinical finding. This is corroborated by non-covalent interaction (NCI) analysis and DFT calculations. Whereas the MD simulations show a loss of one hydrogen bond upon the resistance mutation, NCI and energy decomposition analysis (EDA) reveal that a multitude of interactions are weakened.

GROMACS is a widely-used molecular dynamics software package with a focus on performance, portability, and maintainability across a broad range of platforms. Thanks to its early algorithmic redesign and flexible heterogeneous parallelization, GROMACS has successfully harnessed GPU accelerators for more than a decade. With the diversification of accelerator platforms in HPC and no obvious choice for a multi-vendor programming model, the GROMACS project found itself at a crossroads. The performance and portability requirements, and a strong preference for a standards-based solution, motivated our choice to use SYCL on both new HPC GPU platforms: AMD and Intel. Since the GROMACS 2022 release, the SYCL backend has been the primary means to target AMD GPUs in preparation for exascale HPC architectures like LUMI and Frontier. SYCL is a cross-platform, royalty-free, C++17-based standard for programming hardware accelerators. It allows using the same code to target GPUs from all three major vendors with minimal specialization. While SYCL implementations build on native toolchains, performance of such an approach is not immediately evident. Biomolecular simulations have challenging performance characteristics: latency sensitivity, the need for strong scaling, and typical iteration times as short as hundreds of microseconds. Hence, obtaining good performance across the range of problem sizes and scaling regimes is particularly challenging. Here, we share the results of our work on readying GROMACS for AMD GPU platforms using SYCL, and demonstrate performance on Cray EX235a machines with MI250X accelerators. Our findings illustrate that portability is possible without major performance compromises. We provide a detailed analysis of node-level kernel and runtime performance with the aim of sharing best practices with the HPC community on using SYCL as a performance-portable GPU framework., Comment: 14 pages, 9 figures, presented at Cray User Group 2024

Our skin constitutes an effective permeability barrier that protects the body from exogenous substances but concomitantly severely limits the number of pharmaceutical drugs that can be delivered transdermally. In topical formulation design, chemical permeation enhancers (PEs) are used to increase drug skin permeability. In vitro skin permeability experiments can measure net effects of PEs on transdermal drug transport, but they cannot explain the molecular mechanisms of interactions between drugs, permeation enhancers, and skin structure, which limits the possibility to rationally design better new drug formulations. Here we investigate the effect of the PEs water, lauric acid, geraniol, stearic acid, thymol, ethanol, oleic acid, and eucalyptol on the transdermal transport of metronidazole, caffeine, and naproxen. We use atomistic molecular dynamics (MD) simulations in combination with developed molecular models to calculate the free energy difference between 11 PE-containing formulations and the skin’s barrier structure. We then utilize the results to calculate the final concentration of PEs in skin. We obtain an RMSE of 0.58 log units for calculated partition coefficients from water into the barrier structure. We then use the modified PE-containing barrier structure to calculate the PEs’ permeability enhancement ratios (ERs) on transdermal metronidazole, caffeine, and naproxen transport and compare with the results obtained from in vitro experiments. We show that MD simulations are able to reproduce rankings based on ERs. However, strict quantitative correlation with experimental data needs further refinement, which is complicated by significant deviations between different measurements. Finally, we propose a model for how to use calculations of the potential of mean force of drugs across the skin’s barrier structure in a topical formulation design., QC 20231114

Ligand-gated ion channels transduce electrochemical signals in neurons and other excitable cells. Aside from canonical ligands, phospholipids are thought to bind specifically to the transmembrane domain of several ion channels. However, structural details of such lipid contacts remain elusive, partly due to limited resolution of these regions in experimental structures. Here, we discovered multiple lipid interactions in the channel GLIC by integrating cryo-electron microscopy and large-scale molecular simulations. We identified 25 bound lipids in the GLIC closed state, a conformation where none, to our knowledge, were previously known. Three lipids were associated with each subunit in the inner leaflet, including a buried interaction disrupted in mutant simulations. In the outer leaflet, two intrasubunit sites were evident in both closed and open states, while a putative intersubunit site was preferred in open-state simulations. This work offers molecular details of GLIC-lipid contacts particularly in the ill-characterized closed state, testable hypotheses for state-dependent binding, and a multidisciplinary strategy for modeling protein-lipid interactions.

The resolution revolution has increasingly enabled single-particle cryogenic electron microscopy (cryo-EM) reconstructions of previously inaccessible systems, including membrane proteins—a category that constitutes a disproportionate share of drug targets. We present a protocol for using density-guided molecular dynamics simulations to automatically refine atomistic models into membrane protein cryo-EM maps. Using adaptive force density-guided simulations as implemented in the GROMACS molecular dynamics package, we show how automated model refinement of a membrane protein is achieved without the need to manually tune the fitting force ad hoc. We also present selection criteria to choose the best-fit model that balances stereochemistry and goodness of fit. The proposed protocol was used to refine models into a new cryo-EM density of the membrane protein maltoporin, either in a lipid bilayer or detergent micelle, and we found that results do not substantially differ from fitting in solution. Fitted structures satisfied classical model-quality metrics and improved the quality and the model-to-map correlation of the x-ray starting structure. Additionally, the density-guided fitting in combination with generalized orientation-dependent all-atom potential was used to correct the pixel-size estimation of the experimental cryo-EM density map. This work demonstrates the applicability of a straightforward automated approach to fitting membrane protein cryo-EM densities. Such computational approaches promise to facilitate rapid refinement of proteins under different conditions or with various ligands present, including targets in the highly relevant superfamily of membrane proteins.

Exascale computing has been a dream for ages and is close to becoming a reality that will impact how molecular simulations are being performed, as well as the quantity and quality of the information derived for them. We review how the biomolecular simulations field is anticipating these new architectures, making emphasis on recent work from groups in the BioExcel Center of Excellence for High Performance Computing. We exemplified the power of these simulation strategies with the work done by the HPC simulation community to fight Covid-19 pandemics.

Exascale computing has been a dream for ages and is close to becoming a reality that will impact how molecular simulations are being performed, as well as the quantity and quality of the information derived for them. We review how the biomolecular simulations field is anticipating these new architectures, making emphasis on recent work from groups in the BioExcel Center of Excellence for High Performance Computing. We exemplified the power of these simulation strategies with the work done by the HPC simulation community to fight Covid-19 pandemics. This article is categorized under: Data Science > Computer Algorithms and Programming Data Science > Databases and Expert Systems Molecular and Statistical Mechanics > Molecular Dynamics and Monte-Carlo Methods., QC 20230227

Better detectors and automated data collection have generated a flood of high-resolution cryo-EM maps, which in turn has renewed interest in improving methods for determining structure models corresponding to these maps. However, automatically fitting atoms to densities becomes difficult as their resolution increases and the refinement potential has a vast number of local minima. In practice, the problem becomes even more complex when one also wants to achieve a balance between a good fit of atom positions to the map, while also establishing good stereochemistry or allowing protein secondary structure to change during fitting. Here, we present a solution to this challenge using a maximum likelihood approach by formulating the problem as identifying the structure most likely to have produced the observed density map. This allows us to derive new types of smooth refinement potential-based on relative entropy-in combination with a novel adaptive force scaling algorithm to allow balancing of force-field and density-based potentials. In a low-noise scenario, as expected from modern cryo-EM data, the relative-entropy based refinement potential outperforms alternatives, and the adaptive force scaling appears to aid all existing refinement potentials. The method is available as a component in the GROMACS molecular simulation toolkit. Author summaryCryo-electron microscopy has gone through a revolution and now regularly produces data with 2 & ANGS; resolution. However, this data comes in the shape of density maps, and fitting atomic coordinates into these maps can be a labor-intensive and challenging problem. This is particularly valid when there are multiple conformations, flexible regions, or parts of the structure with lower resolution. In many cases it is also desirable to to understand how a molecule moves between such conformations. This can be addressed with molecular dynamics simulations using densities as target restraints, but the refinement potentials commonly

Our skin constitutes an effective permeability barrier that protects the body from exogenous substances but concomitantly severely limits the number of pharmaceutical drugs that can be delivered transdermally. In topical formulation design, chemical permeation enhancers (PEs) are used to increase drug skin permeability. In vitro skin permeability experiments can measure net effects of PEs on transdermal drug transport, but they cannot explain the molecular mechanisms of interactions between drugs, permeation enhancers, and skin structure, which limits the possibility to rationally design better new drug formulations. Here we investigate the effect of the PEs water, lauric acid, geraniol, stearic acid, thymol, ethanol, oleic acid, and eucalyptol on the transdermal transport of metronidazole, caffeine, and naproxen. We use atomistic molecular dynamics (MD) simulations in combination with developed molecular models to calculate the free energy difference between 11 PE-containing formulations and the skin’s barrier structure. We then utilize the results to calculate the final concentration of PEs in skin. We obtain an RMSE of 0.58 log units for calculated partition coefficients from water into the barrier structure. We then use the modified PE-containing barrier structure to calculate the PEs’ permeability enhancement ratios (ERs) on transdermal metronidazole, caffeine, and naproxen transport and compare with the results obtained from in vitro experiments. We show that MD simulations are able to reproduce rankings based on ERs. However, strict quantitative correlation with experimental data needs further refinement, which is complicated by significant deviations between different measurements. Finally, we propose a model for how to use calculations of the potential of mean force of drugs across the skin’s barrier structure in a topical formulation design.

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Today digital revolution is having a dramatic impact on the pharmaceutical industry and the entire healthcare system. The implementation of machine learning, extreme-scale computer simulations, and big data analytics in the drug design and development process offers an excellent opportunity to lower the risk of investment and reduce the time to the patient. Within the LIGATE project 1, we aim to integrate, extend, and co-design best-in-class European components to design Computer-Aided Drug Design (CADD) solutions exploiting today's high-end supercomputers and tomorrow's Exascale resources, fostering European competitiveness in the field. The proposed LIGATE solution is a fully integrated workflow that enables to deliver the result of a virtual screening campaign for drug discovery with the highest speed along with the highest accuracy. The full automation of the solution and the possibility to run it on multiple supercomputing centers at once permit to run an extreme scale in silico drug discovery campaign in few days to respond promptly for example to a worldwide pandemic crisis., Part of ISBN 9798400701405QC 20230919

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QC 20230911

The resolution revolution has increasingly enabled single-particle cryogenic electron microscopy (cryo-EM) reconstructions of previously inaccessible systems, including membrane proteins—a category that constitutes a disproportionate share of drug targets. We present a protocol for using density-guided molecular dynamics simulations to automatically refine atomistic models into membrane protein cryo-EM maps. Using adaptive force density-guided simulations as implemented in the GROMACS molecular dynamics package, we show how automated model refinement of a membrane protein is achieved without the need to manually tune the fitting force ad hoc. We also present selection criteria to choose the best-fit model that balances stereochemistry and goodness of fit. The proposed protocol was used to refine models into a new cryo-EM density of the membrane protein maltoporin, either in a lipid bilayer or detergent micelle, and we found that results do not substantially differ from fitting in solution. Fitted structures satisfied classical model-quality metrics and improved the quality and the model-to-map correlation of the x-ray starting structure. Additionally, the density-guided fitting in combination with generalized orientation-dependent all-atom potential was used to correct the pixel-size estimation of the experimental cryo-EM density map. This work demonstrates the applicability of a straightforward automated approach to fitting membrane protein cryo-EM densities. Such computational approaches promise to facilitate rapid refinement of proteins under different conditions or with various ligands present, including targets in the highly relevant superfamily of membrane proteins., QC 20231123

Better detectors and automated data collection have generated a flood of high-resolution cryo-EM maps, which in turn has renewed interest in improving methods for determining structure models corresponding to these maps. However, automatically fitting atoms to densities becomes difficult as their resolution increases and the refinement potential has a vast number of local minima. In practice, the problem becomes even more complex when one also wants to achieve a balance between a good fit of atom positions to the map, while also establishing good stereochemistry or allowing protein secondary structure to change during fitting. Here, we present a solution to this challenge using a maximum likelihood approach by formulating the problem as identifying the structure most likely to have produced the observed density map. This allows us to derive new types of smooth refinement potential-based on relative entropy-in combination with a novel adaptive force scaling algorithm to allow balancing of force-field and density-based potentials. In a low-noise scenario, as expected from modern cryo-EM data, the relative-entropy based refinement potential outperforms alternatives, and the adaptive force scaling appears to aid all existing refinement potentials. The method is available as a component in the GROMACS molecular simulation toolkit. Author summaryCryo-electron microscopy has gone through a revolution and now regularly produces data with 2 & ANGS; resolution. However, this data comes in the shape of density maps, and fitting atomic coordinates into these maps can be a labor-intensive and challenging problem. This is particularly valid when there are multiple conformations, flexible regions, or parts of the structure with lower resolution. In many cases it is also desirable to to understand how a molecule moves between such conformations. This can be addressed with molecular dynamics simulations using densities as target restraints, but the refinement potentials commonly, QC 20230824

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QC 20230911

QC 20230911

Exascale computing has been a dream for ages and is close to becoming a reality that will impact how molecular simulations are being performed, as well as the quantity and quality of the information derived for them. We review how the biomolecular simulations field is anticipating these new architectures, making emphasis on recent work from groups in the BioExcel Center of Excel-lence for High Performance Computing. We exemplified the power of these simulation strategies with the work done by the HPC simulation community to fight Covid-19 pandemics., European Commission (BioExcel-2project), Grant/Award Number: 823830; Instituto de Salud Carlos III, Grant/AwardNumber: PT17/0009/0007; Ministerio de Ciencia e Innovación, Grant/Award Numbers: PID2020-116620GB-I00, RTI2018-096704-B-100., Peer Reviewed, Postprint (author's final draft)

A molecular-level understanding of skin permeation may rationalize and streamline product development, and improve quality and control, of transdermal and topical drug delivery systems. It may also facilitate toxicity and safety assessment of cosmetics and skin care products. Here, we present new molecular dynamics simulation approaches that make it possible to efficiently sample the free energy and local diffusion coefficient across the skin’s barrier structure to predict skin permeability and the effects of chemical penetration enhancers. In particular, we introduce a new approach to use two-dimensional reaction coordinates in the accelerated weight histogram method, where we combine sampling along spatial coordinates with an alchemical perturbation virtual coordinate. We present predicted properties for 20 permeants, and demonstrate how our approach improves correlation with ex vivo/in vitro skin permeation data. For the compounds included in this study, the obtained log KPexp-calc mean square difference was 0.9 cm2 h−2.

Pentameric ligand-gated ion channels (pLGICs) perform electrochemical signal transduction in organisms ranging from bacteria to humans. Among the prokaryotic pLGICs, there is architectural diversity involving N-terminal domains (NTDs) not found in eukaryotic relatives, exemplified by the calcium-sensitive channel (DeCLIC) from a Desulfofustis deltaproteobacterium, which has an NTD in addition to the canonical pLGIC structure. Here, we have characterized the structure and dynamics of DeCLIC through cryoelectron microscopy (cryo-EM), small-angle neutron scattering (SANS), and molecular dynamics (MD) simulations. In the presence and absence of calcium, cryo-EM yielded structures with alternative conformations of the calcium-binding site. SANS profiles further revealed conformational diversity at room temperature beyond that observed in static structures, shown through MD to be largely attributable to rigid-body motions of the NTD relative to the protein core, with expanded and asymmetric conformations improving the fit of the SANS data. This work reveals the range of motion available to the DeCLIC NTD and calcium-binding site, expanding the conformational landscape of the pLGIC family. Further, these findings demonstrate the power of combining low-resolution scattering, high-resolution structural, and MD simulation data to elucidate interfacial interactions that are highly conserved in the pLGIC family.

SARS-CoV-2 contains four structural proteins in its genome. These proteins aid in the assembly and budding of new virions at the ER-Golgi intermediate compartment (ERGIC). Current fundamental research efforts largely focus on one of these proteins – the spike (S) protein. Since successful antiviral therapies are likely to target multiple viral components, there is considerable interest in understanding the biophysical role of its other structural proteins, in particular structural membrane proteins. Here, we have focused our efforts on the characterization of the full-length envelope (E) protein from SARS-CoV-2, combining experimental and computational approaches. Recombinant expression of the full-length E protein from SARS-CoV-2 reveals that this membrane protein is capable of independent multimerization, possibly as a tetrameric or smaller species. Fluorescence microscopy shows that the protein localizes intracellularly, and coarse-grained MD simulations indicate it causes bending of the surrounding lipid bilayer, corroborating a potential role for the E protein in viral budding. Although we did not find robust electrophysiological evidence of ion-channel activity, cells transfected with the E protein exhibited reduced intracellular Ca2+, which may further promote viral replication. However, our atomistic MD simulations revealed that previous NMR structures are relatively unstable, and result in models incapable of ion conduction. Our study highlights the importance of using high-resolution structural data obtained from a full-length protein to gain detailed molecular insights, and eventually permitting virtual drug screening.

Tungsten carbonitride [W(C,N)] was deposited on cemented carbide substrates by chemical vapor deposition (CVD) in a hot-wall reactor using tungsten hexafluoride (WF6), acetonitrile (CH3CN), and hydrogen (H-2) as precursors. Tungsten carbides and nitrides with a hexagonal 6-WC type structure are generally difficult to obtain by CVD. Here, it was found that the combination of WF6 and CH3CN precursors enabled the deposition of W(C,N) coatings with a delta-WC type structure and columnar grains. A process window as a function of the deposition temperature and precursor partial pressures was determined to establish the conditions for the deposition of such coatings. Scanning electron microscopy, x-ray diffraction, electron backscatter diffraction, and elastic recoil detection analysis were used for the investigation of the coating thickness, microstructure, texture, and composition. From the investigation of the kinetics, it was concluded that the growth was mainly controlled by surface kinetics with an apparent activation energy of 77 kJ/mol, yielding an excellent step coverage. The partial reaction orders of the reactants together with their influence on the microstructure and coating composition was further used to gain a deeper understanding of the growth mechanism. Within the process window, the microstructure and the texture of the W(C,N) coatings could be tailored by the process parameters, enabling microstructural engineering with tuning of the mechanical properties of the W(C,N) coatings. The nanoindentation hardness (36.6-45.7 GPa) and elastic modulus (564-761 GPa) were found to be closely related to the microstructure.

Tungsten carbonitride [W(C,N)] was deposited on cemented carbide substrates by chemical vapor deposition (CVD) in a hot-wall reactor using tungsten hexafluoride (WF6), acetonitrile (CH3CN), and hydrogen (H-2) as precursors. Tungsten carbides and nitrides with a hexagonal 6-WC type structure are generally difficult to obtain by CVD. Here, it was found that the combination of WF6 and CH3CN precursors enabled the deposition of W(C,N) coatings with a delta-WC type structure and columnar grains. A process window as a function of the deposition temperature and precursor partial pressures was determined to establish the conditions for the deposition of such coatings. Scanning electron microscopy, x-ray diffraction, electron backscatter diffraction, and elastic recoil detection analysis were used for the investigation of the coating thickness, microstructure, texture, and composition. From the investigation of the kinetics, it was concluded that the growth was mainly controlled by surface kinetics with an apparent activation energy of 77 kJ/mol, yielding an excellent step coverage. The partial reaction orders of the reactants together with their influence on the microstructure and coating composition was further used to gain a deeper understanding of the growth mechanism. Within the process window, the microstructure and the texture of the W(C,N) coatings could be tailored by the process parameters, enabling microstructural engineering with tuning of the mechanical properties of the W(C,N) coatings. The nanoindentation hardness (36.6-45.7 GPa) and elastic modulus (564-761 GPa) were found to be closely related to the microstructure.

Tungsten carbonitride [W(C,N)] was deposited on cemented carbide substrates by chemical vapor deposition (CVD) in a hot-wall reactor using tungsten hexafluoride (WF6), acetonitrile (CH3CN), and hydrogen (H-2) as precursors. Tungsten carbides and nitrides with a hexagonal 6-WC type structure are generally difficult to obtain by CVD. Here, it was found that the combination of WF6 and CH3CN precursors enabled the deposition of W(C,N) coatings with a delta-WC type structure and columnar grains. A process window as a function of the deposition temperature and precursor partial pressures was determined to establish the conditions for the deposition of such coatings. Scanning electron microscopy, x-ray diffraction, electron backscatter diffraction, and elastic recoil detection analysis were used for the investigation of the coating thickness, microstructure, texture, and composition. From the investigation of the kinetics, it was concluded that the growth was mainly controlled by surface kinetics with an apparent activation energy of 77 kJ/mol, yielding an excellent step coverage. The partial reaction orders of the reactants together with their influence on the microstructure and coating composition was further used to gain a deeper understanding of the growth mechanism. Within the process window, the microstructure and the texture of the W(C,N) coatings could be tailored by the process parameters, enabling microstructural engineering with tuning of the mechanical properties of the W(C,N) coatings. The nanoindentation hardness (36.6-45.7 GPa) and elastic modulus (564-761 GPa) were found to be closely related to the microstructure.

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The intracellular domain (ICD) of Cys-loop receptors mediates diverse functions. To date, no structure of a full-length ICD is available due to challenges stemming from its dynamic nature. Here, combining nuclear magnetic resonance (NMR) and electron spin resonance experiments with Rosetta computations, we determine full-length ICD structures of the human alpha 7 nicotinic acetylcholine receptor in a resting state. We show that similar to 57% of the ICD residues are in highly flexible regions, primarily in a large loop (loop L) with the most mobile segment spanning similar to 50 angstrom from the central channel axis. Loop L is anchored onto the MA helix and virtually forms two smaller loops, thereby increasing its stability. Previously known motifs for cytoplasmic binding, regulation, and signaling are found in both the helices and disordered flexible regions, supporting the essential role of the ICD conformational plasticity in orchestrating a broad range of biological processes., QC 20220304

Tungsten carbonitride [W(C,N)] was deposited on cemented carbide substrates by chemical vapor deposition (CVD) in a hot-wall reactor using tungsten hexafluoride (WF6), acetonitrile (CH3CN), and hydrogen (H-2) as precursors. Tungsten carbides and nitrides with a hexagonal 6-WC type structure are generally difficult to obtain by CVD. Here, it was found that the combination of WF6 and CH3CN precursors enabled the deposition of W(C,N) coatings with a delta-WC type structure and columnar grains. A process window as a function of the deposition temperature and precursor partial pressures was determined to establish the conditions for the deposition of such coatings. Scanning electron microscopy, x-ray diffraction, electron backscatter diffraction, and elastic recoil detection analysis were used for the investigation of the coating thickness, microstructure, texture, and composition. From the investigation of the kinetics, it was concluded that the growth was mainly controlled by surface kinetics with an apparent activation energy of 77 kJ/mol, yielding an excellent step coverage. The partial reaction orders of the reactants together with their influence on the microstructure and coating composition was further used to gain a deeper understanding of the growth mechanism. Within the process window, the microstructure and the texture of the W(C,N) coatings could be tailored by the process parameters, enabling microstructural engineering with tuning of the mechanical properties of the W(C,N) coatings. The nanoindentation hardness (36.6-45.7 GPa) and elastic modulus (564-761 GPa) were found to be closely related to the microstructure.

Inhibitors that bind competitively to the ATP binding pocket in the kinase domain of the oncogenic fusion protein BCR-Abl1 are used successfully in targeted therapy of chronic myeloid leukemia (CML). Such inhibitors provided the first proof of concept that kinase inhibition can succeed in a clinical setting. However, emergence of drug resistance and dose-dependent toxicities limit the effectiveness of these drugs. Therefore, treatment with a combination of drugs without overlapping resistance mechanisms appears to be an appropriate strategy. In the present work, we explore the effectiveness of combination therapies of the recently developed allosteric inhibitor asciminib with the ATP-competitive inhibitors nilotinib and dasatinib in inhibiting the BCR-Abl1 kinase activity in CML cell lines. Through these experiments, we demonstrate that asciminib significantly enhances the inhibition activity of nilotinib, but not of dasatinib. Exploring molecular mechanisms for such allosteric enhancement via systematic computational investigation incorporating molecular dynamics, metadynamics simulations, and density functional theory calculations, we found two distinct contributions. First, binding of asciminib triggers conformational changes in the inactive state of the protein, thereby making the activation process less favorable by similar to 4 kcal/mol. Second, the binding of asciminib decreases the binding free energies of nilotinib by similar to 3 and similar to 7 kcal/mol for the wildtype and T315I-mutated protein, respectively, suggesting the possibility of reducing nilotinib dosage and lowering risk of developing resistance in the treatment of CML.