AlphaFold2 knows some protein folding principles.

AlphaFold2 (AF2) has revolutionized protein structure prediction. However, a common confusion lies in equating the protein structure prediction problem with the protein folding problem. The former provides a static structure, while the latter explains the dynamic folding pathway to that structure. We challenge the current status quo and advocate that AF2 has indeed learned some protein folding principles, despite being designed for structure prediction. AF2's high-dimensional parameters encode an imperfect biophysical scoring function. Typically, AF2 uses multiple sequence alignments (MSAs) to guide the search within a narrow region of its learned surface. In our study, we operate AF2 without MSAs or initial templates, forcing it to sample its entire energy landscape - more akin to an ab initio approach. Among over 7,000 proteins, a fraction fold using sequence alone, highlighting the smoothness of AF2's learned energy surface. Additionally, by combining recycling and iterative predictions, we discover multiple AF2 intermediate structures in good agreement with known experimental data. AF2 appears to follow a "local first, global later" folding mechanism. For designed proteins with more optimized local interactions, AF2's energy landscape is too smooth to detect intermediates even when it should. Our current work sheds new light on what AF2 has learned and opens exciting possibilities to advance our understanding of protein folding and for experimental discovery of folding intermediates.

Spectral analysis comparison of pushbroom and snapshot hyperspectral cameras for in vivo brain tissues and chromophore identification.

Significance: Hyperspectral imaging sensors have rapidly advanced, aiding in tumor diagnostics for in vivo brain tumors. Linescan cameras effectively distinguish between pathological and healthy tissue, whereas snapshot cameras offer a potential alternative to reduce acquisition time. Aim: Our research compares linescan and snapshot hyperspectral cameras for in vivo brain tissues and chromophore identification. Approach: We compared a linescan pushbroom camera and a snapshot camera using images from 10 patients with various pathologies. Objective comparisons were made using unnormalized and normalized data for healthy and pathological tissues. We utilized the interquartile range (IQR) for the spectral angle mapping (SAM), the goodness-of-fit coefficient (GFC), and the root mean square error (RMSE) within the 659.95 to 951.42 nm range. In addition, we assessed the ability of both cameras to capture tissue chromophores by analyzing absorbance from reflectance information. Results: The SAM metric indicates reduced dispersion and high similarity between cameras for pathological samples, with a 9.68% IQR for normalized data compared with 2.38% for unnormalized data. This pattern is consistent across GFC and RMSE metrics, regardless of tissue type. Moreover, both cameras could identify absorption peaks of certain chromophores. For instance, using the absorbance measurements of the linescan camera, we obtained SAM values below 0.235 for four peaks, regardless of the tissue and type of data under inspection. These peaks are one for cytochrome b in its oxidized form at λ = 422 nm , two for HbO 2 at λ = 542 nm and λ = 576 nm , and one for water at λ = 976 nm . Conclusion: The spectral signatures of the cameras show more similarity with unnormalized data, likely due to snapshot sensor noise, resulting in noisier signatures post-normalization. Comparisons in this study suggest that snapshot cameras might be viable alternatives to linescan cameras for real-time brain tissue identification.

Implementing and Evaluating the Timed up and Go Test Automation Using Smartphones and Smartwatches.

Physical performance tests aim to assess the physical abilities and mobility skills of individuals for various healthcare purposes. They are often driven by experts and usually performed at their practice, and therefore they are resource-intensive and time-demanding. For tests based on objective measurements (e.g., duration, repetitions), technology can be used to automate them, allowing the patients to perform the test themselves, more frequently and anywhere, while alleviating the expert from supervising the test. The well-known Timed Up and Go (TUG) test, typically used for mobility assessment, is an ideal candidate for automation, as inertial sensors (among others) can be deployed to detect the various movements constituting the test without expert supervision. To move from expert-led testing to self-administered testing, we present a mHealth system capable of automating the TUG test using a pocket-sized smartphone or a wrist smartwatch paired with a smartphone, where data from inertial sensors are used to detect the activities carried out by the patient while performing the test and compute their results in real time. All processing (i.e., data processing, machine learning-based activity inference, results calculation) takes place on the smartphone. The use of both devices to automate the TUG test was evaluated (w.r.t. accuracy, reliability and battery consumption) and mutually compared, and set off with a reference method, obtaining excellent Bland-Altman agreement results and Intraclass Correlation Coefficient reliability. Results also suggest that the smartwatch-based system performs better than the smartphone-based system.

Precision or Personalized Nutrition: A Bibliometric Analysis.

Food systems face the challenge of maintaining adequate nutrition for all populations. Inter-individual responses to the same diet have made precision or personalized nutrition (PN) an emerging and relevant topic. The aim of this study is to analyze the evolution of the PN field, identifying the principal actors and topics, and providing a comprehensive overview. Therefore, a bibliometric analysis of the scientific research available through the Web of Science (WOS) database was performed, revealing 2148 relevant papers up to June 2024. VOSviewer and the WOS platform were employed for the processing and analysis, and included an evaluation of diverse data such as country, author or most frequent keywords, among others. The analysis revealed a period of exponential growth from 2015 to 2023, with the USA, Spain, and England as the top contributors. The field of "Nutrition and Dietetics" is particularly significant, comprising nearly 33% of the total publications. The most highly cited institutions are the universities of Tufts, College Dublin, and Navarra. The relationship between nutrition, genetics, and omics sciences, along with dietary intervention studies, has been a defining factor in the evolution of PN. In conclusion, PN represents a promising field of research with significant potential for further advancement and growth.

Cost-benefit analysis of the National Immunization Program in Spain.

Broad benefits of vaccination programs are well acknowledged but difficult to measure, especially when considering all vaccines included in a National Immunization Program (NIP). The aim was to conduct a cost-benefit analysis of the entire NIP in Spain, and an expanded NIP including four potential additional programs. A cost-benefit analysis was performed in Excel to assess the economic and health benefits (€) of vaccinating a single cohort of newborns over a lifetime horizon compared to no vaccination, from a societal perspective: firstly, according to the 2020 NIP in Spain (including 2021 recommendation for herpes zoster in 65-year-olds); and secondly, with an expanded NIP (adding rotavirus and meningococcal B in infants, and pertussis booster in adults aged >65 years and herpes zoster in all adults >50 years). The main inputs were taken from published literature and Spanish databases. Results were presented as a benefit-cost ratio (economic benefit per €1 invested). A cohort of 343,126 newborns were included in the analysis. The total investment needed to vaccinate the cohort throughout their lifetime, according to the 2020 NIP and the expanded NIP, was estimated at €168.5 million and €275.5 million, respectively. Potential economic benefits were €772.2 million and €803.0 million, respectively. The societal benefit-cost ratio was €4.58 and €2.91 per €1 invested, respectively. Even with the addition of new vaccination programs, the Spanish NIP yielded positive benefit-cost ratios from the societal perspective, demonstrating that NIPs spanning the full life course are an efficient public health measure.

A Platform for Ultra-Fast Proton Probing of Matter in Extreme Conditions.

Recent developments in ultrashort and intense laser systems have enabled the generation of short and brilliant proton sources, which are valuable for studying plasmas under extreme conditions in high-energy-density physics. However, developing sensors for the energy selection, focusing, transport, and detection of these sources remains challenging. This work presents a novel and simple design for an isochronous magnetic selector capable of angular and energy selection of proton sources, significantly reducing temporal spread compared to the current state of the art. The isochronous selector separates the beam based on ion energy, making it a potential component in new energy spectrum sensors for ions. Analytical estimations and Monte Carlo simulations validate the proposed configuration. Due to its low temporal spread, this selector is also useful for studying extreme states of matter, such as proton stopping power in warm dense matter, where short plasma stagnation time (<100 ps) is a critical factor. The proposed selector can also be employed at higher proton energies, achieving final time spreads of a few picoseconds. This has important implications for sensing technologies in the study of coherent energy deposition in biology and medical physics.

Protein Retrieval via Integrative Molecular Ensembles (PRIME) through Extended Similarity Indices.

Molecular dynamics (MD) simulations are ideally suited to describe conformational ensembles of biomolecules such as proteins and nucleic acids. Microsecond-long simulations are now routine, facilitated by the emergence of graphical processing units. Clustering, which groups objects based on structural similarity, is typically used to process ensembles, leading to different states, their populations, and the identification of representative structures. A popular pipeline combines hierarchical clustering for clustering and selecting the cluster centroid as representative of the cluster. Here, we propose to improve on this approach, by developing a module-Protein Retrieval via Integrative Molecular Ensembles (PRIME), that consists of tools to improve the prediction of the representative in the most populated cluster using extended continuous similarity. PRIME is integrated with our Molecular Dynamics Analysis with N-ary Clustering Ensembles (MDANCE) package and can be used as a postprocessing tool for arbitrary clustering algorithms, compatible with several MD suites. PRIME predictions produced structures that when aligned to the experimental structure were better superposed (lower RMSD). A further benefit of PRIME is its linear scaling─rather than the traditional O(N2) traditionally associated with comparisons of elements in a set.

Targeting IGF2 to reprogram the tumor microenvironment for enhanced viro-immunotherapy.

BACKGROUND: The FDA approval of oncolytic herpes simplex-1 virus (oHSV) therapy underscores its therapeutic promise and safety as a cancer immunotherapy. Despite this promise, the current efficacy of oHSV is significantly limited to a small subset of patients largely due to the resistance in tumor and tumor microenvironment (TME). METHODS: RNA sequencing (RNA-Seq) was used to identify molecular targets of oHSV resistance. Intracranial human and murine glioma or breast cancer brain metastasis (BCBM) tumor-bearing mouse models were employed to elucidate the mechanism underlying oHSV therapy-induced resistance. RESULTS: Transcriptome analysis identified IGF2 as one of the top-secreted proteins following oHSV treatment. Moreover, IGF2 expression was significantly upregulated in 10 out of 14 recurrent GBM patients after treatment with oHSV, rQNestin34.5v.2 (71.4%; P = .0020) (ClinicalTrials.gov, NCT03152318). Depletion of IGF2 substantially enhanced oHSV-mediated tumor cell killing in vitro and improved survival of mice bearing BCBM tumors in vivo. To mitigate the oHSV-induced IGF2 in the TME, we constructed a novel oHSV, oHSV-D11mt, secreting a modified IGF2R domain 11 (IGF2RD11mt) that acts as IGF2 decoy receptor. Selective blocking of IGF2 by IGF2RD11mt significantly increased cytotoxicity, reduced oHSV-induced neutrophils/PMN-MDSCs infiltration, and reduced secretion of immune suppressive/proangiogenic cytokines, while increased CD8 + cytotoxic T lymphocytes (CTLs) infiltration, leading to enhanced survival in GBM or BCBM tumor-bearing mice. CONCLUSIONS: This is the first study reporting that oHSV-induced secreted IGF2 exerts a critical role in resistance to oHSV therapy, which can be overcome by oHSV-D11mt as a promising therapeutic advance for enhanced viro-immunotherapy.

Structural Elucidation of Ubiquitin via Gas-Phase Ion/Ion Cross-Linking Reactions Using Sodium-Cationized Reagents Coupled with Infrared Multiphoton Dissociation.

Accurate structural determination of proteins is critical to understanding their biological functions and the impact of structural disruption on disease progression. Gas-phase cross-linking mass spectrometry (XL-MS) via ion/ion reactions between multiply charged protein cations and singly charged cross-linker anions has previously been developed to obtain low-resolution structural information on proteins. This method significantly shortens experimental time relative to conventional solution-phase XL-MS but has several technical limitations: (1) the singly deprotonated N-hydroxysulfosuccinimide (sulfo-NHS)-based cross-linker anions are restricted to attachment at neutral amine groups of basic amino acid residues and (2) analyzing terminal cross-linked fragment ions is insufficient to unambiguously localize sites of linker attachment. Herein, we demonstrate enhanced structural information for alcohol-denatured A-state ubiquitin obtained from an alternative gas-phase XL-MS approach. Briefly, singly sodiated ethylene glycol bis(sulfosuccinimidyl succinate) (sulfo-EGS) cross-linker anions enable covalent cross-linking at both ammonium and amine groups. Additionally, covalently modified internal fragment ions, along with terminal b-/y-type counterparts, improve the determination of linker attachment sites. Molecular dynamics simulations validate experimentally obtained gas-phase conformations of denatured ubiquitin. This method has identified four cross-linking sites across 8+ ubiquitin, including two new sites in the N-terminal region of the protein that were originally inaccessible in prior gas-phase XL approaches. The two N-terminal cross-linking sites suggest that the N-terminal half of ubiquitin is more compact in gas-phase conformations. By comparison, the two C-terminal linker sites indicate the signature transformation of this region of the protein from a native to a denatured conformation. Overall, the results suggest that the solution-phase secondary structures of the A-state ubiquitin are conserved in the gas phase. This method also provides sufficient sensitivity to differentiate between two gas-phase conformers of the same charge state with subtle structural variations.

Etiological diagnosis of recurrent acute pancreatitis.

Acute pancreatitis is the leading cause of inpatient care among gastrointestinal conditions. Despite early intervention, one-third of patients experience recurrent acute pancreatitis (RAP). A comprehensive diagnostic approach is warranted to identify and treat underlying factors in order to prevent recurrence. RAP is most frequent among men aged 30-40, smokers, and in those with excessive alcohol consumption. To identify the etiology is paramount to stratify patients according to their individual risk of RAP and for predicting an eventual evolution to chronic pancreatitis. Although the initial management of acute pancreatitis is widely homogeneous according to established guidelines, there are no defined protocols to investigate RAP. In the present editorial article we propose a structured algorithm with precise recommendations to investigate the etiology RAP as part of routine clinical practice. Although there are relevant knowledge gaps in this disease, we believe that our guidance would contribute for a more homogenous diagnostic approach of RAP in clinical practice.

A Computational Pipeline for Accurate Prioritization of Protein-Protein Binding Candidates in High-Throughput Protein Libraries.

Identifying the interactome for a protein of interest is challenging due to the large number of possible binders. High-throughput experimental approaches narrow down possible binding partners but often include false positives. Furthermore, they provide no information about what the binding region is (e.g., the binding epitope). We introduce a novel computational pipeline based on an AlphaFold2 (AF) Competitive Binding Assay (AF-CBA) to identify proteins that bind a target of interest from a pull-down experiment and the binding epitope. Our focus is on proteins that bind the Extraterminal (ET) domain of Bromo and Extraterminal domain (BET) proteins, but we also introduce nine additional systems to show transferability to other peptide-protein systems. We describe a series of limitations to the methodology based on intrinsic deficiencies of AF and AF-CBA to help users identify scenarios where the approach will be most useful. Given the method's speed and accuracy, we anticipate its broad applicability to identify binding epitope regions among potential partners, setting the stage for experimental verification.

Revolutionizing Peptide-Based Drug Discovery: Advances in the Post-AlphaFold Era.

Peptide-based drugs offer high specificity, potency, and selectivity. However, their inherent flexibility and differences in conformational preferences between their free and bound states create unique challenges that have hindered progress in effective drug discovery pipelines. The emergence of AlphaFold (AF) and Artificial Intelligence (AI) presents new opportunities for enhancing peptide-based drug discovery. We explore recent advancements that facilitate a successful peptide drug discovery pipeline, considering peptides' attractive therapeutic properties and strategies to enhance their stability and bioavailability. AF enables efficient and accurate prediction of peptide-protein structures, addressing a critical requirement in computational drug discovery pipelines. In the post-AF era, we are witnessing rapid progress with the potential to revolutionize peptide-based drug discovery such as the ability to rank peptide binders or classify them as binders/non-binders and the ability to design novel peptide sequences. However, AI-based methods are struggling due to the lack of well-curated datasets, for example to accommodate modified amino acids or unconventional cyclization. Thus, physics-based methods, such as docking or molecular dynamics simulations, continue to hold a complementary role in peptide drug discovery pipelines. Moreover, MD-based tools offer valuable insights into binding mechanisms, as well as the thermodynamic and kinetic properties of complexes. As we navigate this evolving landscape, a synergistic integration of AI and physics-based methods holds the promise of reshaping the landscape of peptide-based drug discovery.

An overload of missense variants in the OTOG gene may drive a higher prevalence of familial Meniere disease in the European population.

Meniere disease is a complex inner ear disorder with significant familial aggregation. A differential prevalence of familial MD (FMD) has been reported, being 9-10% in Europeans compared to 6% in East Asians. A broad genetic heterogeneity in FMD has been described, OTOG being the most common mutated gene, with a compound heterozygous recessive inheritance. We hypothesize that an OTOG-related founder effect may explain the higher prevalence of FMD in the European population. Therefore, the present study aimed to compare the allele frequency (AF) and distribution of OTOG rare variants across different populations. For this purpose, the coding regions with high constraint (low density of rare variants) were retrieved in the OTOG coding sequence in Non-Finnish European (NFE).. Missense variants (AF < 0.01) were selected from a 100 FMD patient cohort, and their population AF was annotated using gnomAD v2.1. A linkage analysis was performed, and odds ratios were calculated to compare AF between NFE and other populations. Thirteen rare missense variants were observed in 13 FMD patients, with 2 variants (rs61978648 and rs61736002) shared by 5 individuals and another variant (rs117315845) shared by two individuals. The results confirm the observed enrichment of OTOG rare missense variants in FMD. Furthermore, eight variants were enriched in the NFE population, and six of them were in constrained regions. Structural modeling predicts five missense variants that could alter the otogelin stability. We conclude that several variants reported in FMD are in constraint regions, and they may have a founder effect and explain the burden of FMD in the European population.

Loop diuretic down-titration at discharge in patients hospitalized for acute heart failure.

AIMS: The current literature provides limited guidance on the best diuretic strategy post-hospitalization for acute heart failure (AHF). It is postulated that the efficacy and safety of the outpatient diuretic regimen may be significantly influenced by the degree of fluid overload (FO) encountered during hospitalization. We hypothesize that in patients with more pronounced FO, reducing their regular oral diuretic dosage might be associated with an elevated risk of unfavourable clinical outcomes. METHODS AND RESULTS: It was a retrospective observational study of 410 patients hospitalized for AHF in which the dose of furosemide at admission and discharge was collected. Patients were categorized across diuretic dose status into two groups: (i) the down-titration group and (ii) the stable/up-titration group. FO status was evaluated by a clinical congestion score and circulating biomarkers. The endpoint of interest was the composite of time to all-cause death and/or heart failure readmission. A multivariable Cox proportional hazard regression model was constructed to analyse the endpoints. The median age was 86 (78-92) years, 256 (62%) were women, and 80% had heart failure with preserved ejection fraction. After multivariate adjustment, the down-titration furosemide equivalent dose remained not associated with the risk of the combined endpoint in the whole sample (hazard ratio 1.34, 95% confidence interval 0.86-2.06, P = 0.184). The risk of the combination of death and/or worsening heart failure associated with the diuretic strategy at discharge was significantly influenced by FO status, including clinical congestion scores and circulating proxies of FO like BNP and cancer antigen 125. CONCLUSIONS: In patients hospitalized for AHF, furosemide down-titration does not imply an increased risk of mortality and/or heart failure readmission. However, FO status modifies the effect of down-titration on the outcome. In patients with severe congestion or residual congestion at discharge, down-titration was associated with an increased risk of mortality and/or heart failure readmission.

Sifting Through the Noise: A Computational Pipeline for Accurate Prioritization of Protein-Protein Binding Candidates in High-Throughput Protein Libraries.

Identifying the interactome for a protein of interest is challenging due to the large number of possible binders. High-throughput experimental approaches narrow down possible binding partners, but often include false positives. Furthermore, they provide no information about what the binding region is (e.g. the binding epitope). We introduce a novel computational pipeline based on an AlphaFold2 (AF) Competition Assay (AF-CBA) to identify proteins that bind a target of interest from a pull-down experiment, along with the binding epitope. Our focus is on proteins that bind the Extraterminal (ET) domain of Bromo and Extraterminal domain (BET) proteins, but we also introduce nine additional systems to show transferability to other peptide-protein systems. We describe a series of limitations to the methodology based on intrinsic deficiencies to AF and AF-CBA, to help users identify scenarios where the approach will be most useful. Given the speed and accuracy of the methodology, we expect it to be generally applicable to facilitate target selection for experimental verification starting from high-throughput protein libraries.

Fully automated CT imaging biomarkers for opportunistic prediction of future hip fractures.

OBJECTIVE: Assess automated CT imaging biomarkers in patients who went on to hip fracture, compared with controls. METHODS: In this retrospective case-control study, 6926 total patients underwent initial abdominal CT over a 20-year interval at one institution. A total of 1308 patients (mean age at initial CT, 70.5 ± 12.0 years; 64.4% female) went on to hip fracture (mean time to fracture, 5.2 years); 5618 were controls (mean age 70.3 ± 12.0 years; 61.2% female; mean follow-up interval 7.6 years). Validated fully automated quantitative CT algorithms for trabecular bone attenuation (at L1), skeletal muscle attenuation (at L3), and subcutaneous adipose tissue area (SAT) (at L3) were applied to all scans. Hazard ratios (HRs) comparing highest to lowest risk quartiles and receiver operating characteristic (ROC) curve analysis including area under the curve (AUC) were derived. RESULTS: Hip fracture HRs (95% CI) were 3.18 (2.69-3.76) for low trabecular bone HU, 1.50 (1.28-1.75) for low muscle HU, and 2.18 (1.86-2.56) for low SAT. 10-year ROC AUC values for predicting hip fracture were 0.702, 0.603, and 0.603 for these CT-based biomarkers, respectively. Multivariate combinations of these biomarkers further improved predictive value; the 10-year ROC AUC combining bone/muscle/SAT was 0.733, while combining muscle/SAT was 0.686. CONCLUSION: Opportunistic use of automated CT bone, muscle, and fat measures can identify patients at higher risk for future hip fracture, regardless of the indication for CT imaging. ADVANCES IN KNOWLEDGE: CT data can be leveraged opportunistically for further patient evaluation, with early intervention as needed. These novel AI tools analyse CT data to determine a patient's future hip fracture risk.

Diversity and prevalence of zoonotic infections at the animal-human interface of primate trafficking in Peru.

Wildlife trafficking creates favorable scenarios for intra- and inter-specific interactions that can lead to parasite spread and disease emergence. Among the fauna affected by this activity, primates are relevant due to their potential to acquire and share zoonoses - infections caused by parasites that can spread between humans and other animals. Though it is known that most primate parasites can affect multiple hosts and that many are zoonotic, comparative studies across different contexts for animal-human interactions are scarce. We conducted a multi-parasite screening targeting the detection of zoonotic infections in wild-caught monkeys in nine Peruvian cities across three contexts: captivity (zoos and rescue centers, n = 187); pet (households, n = 69); and trade (trafficked or recently confiscated, n = 132). We detected 32 parasite taxa including mycobacteria, simian foamyvirus, bacteria, helminths, and protozoa. Monkeys in the trade context had the highest prevalence of hemoparasites (including Plasmodium malariae/brasilianum, Trypanosoma cruzi, and microfilaria) and enteric helminths and protozoa were less common in pet monkeys. However, parasite communities showed overall low variation between the three contexts. Parasite richness (PR) was best explained by host genus and the city where the animal was sampled. Squirrel (genus Saimiri) and wooly (genus Lagothrix) monkeys had the highest PR, which was ~2.2 times the PR found in tufted capuchins (genus Sapajus) and tamarins (genus Saguinus/Leontocebus) in a multivariable model adjusted for context, sex, and age. Our findings illustrate that the threats of wildlife trafficking to One Health encompass exposure to multiple zoonotic parasites well-known to cause disease in humans, monkeys, and other species. We demonstrate these threats continue beyond the markets where wildlife is initially sold; monkeys trafficked for the pet market remain a reservoir for and contribute to the translocation of zoonotic parasites to households and other captive facilities where contact with humans is frequent. Our results have practical applications for the healthcare of rescued monkeys and call for urgent action against wildlife trafficking and ownership of monkeys as pets.

Advancing Molecular Dynamics: Toward Standardization, Integration, and Data Accessibility in Structural Biology.

Molecular dynamics (MD) simulations have become a valuable tool in structural biology, offering insights into complex biological systems that are difficult to obtain through experimental techniques alone. The lack of available data sets and structures in most published computational work has limited other researchers' use of these models. In recent years, the emergence of online sharing platforms and MD database initiatives favor the deposition of ensembles and structures to accompany publications, favoring reuse of the data sets. However, the lack of uniform metadata collection, formats, and what data are deposited limits the impact and its use by different communities that are not necessarily experts in MD. This Perspective highlights the need for standardization and better resource sharing for processing and interpreting MD simulation results, akin to efforts in other areas of structural biology. As the field moves forward, we will see an increase in popularity and benefits of MD-based integrative approaches combining experimental data and simulations through probabilistic reasoning, but these too are limited by uniformity in experimental data availability and choices on how the data are modeled that are not trivial to decipher from papers. Other fields have addressed similar challenges comprehensively by establishing task forces with different degrees of success. The large scope and number of communities to represent the breadth of types of MD simulations complicates a parallel approach that would fit all. Thus, each group typically decides what data and which format to upload on servers like Zenodo. Uploading data with FAIR (findable, accessible, interoperable, reusable) principles in mind including optimal metadata collection will make the data more accessible and actionable by the community. Such a wealth of simulation data will foster method development and infrastructure advancements, thus propelling the field forward.