HybridDBRpred: improved sequence-based prediction of DNA-binding amino acids using annotations from structured complexes and disordered proteins.

Current predictors of DNA-binding residues (DBRs) from protein sequences belong to two distinct groups, those trained on binding annotations extracted from structured protein-DNA complexes (structure-trained) vs. intrinsically disordered proteins (disorder-trained). We complete the first empirical analysis of predictive performance across the structure- and disorder-annotated proteins for a representative collection of ten predictors. Majority of the structure-trained tools perform well on the structure-annotated proteins while doing relatively poorly on the disorder-annotated proteins, and vice versa. Several methods make accurate predictions for the structure-annotated proteins or the disorder-annotated proteins, but none performs highly accurately for both annotation types. Moreover, most predictors make excessive cross-predictions for the disorder-annotated proteins, where residues that interact with non-DNA ligand types are predicted as DBRs. Motivated by these results, we design, validate and deploy an innovative meta-model, hybridDBRpred, that uses deep transformer network to combine predictions generated by three best current predictors. HybridDBRpred provides accurate predictions and low levels of cross-predictions across the two annotation types, and is statistically more accurate than each of the ten tools and baseline meta-predictors that rely on averaging and logistic regression. We deploy hybridDBRpred as a convenient web server at http://biomine.cs.vcu.edu/servers/hybridDBRpred/ and provide the corresponding source code at https://github.com/jianzhang-xynu/hybridDBRpred.

DescribePROT in 2023: more, higher-quality and experimental annotations and improved data download options.

The DescribePROT database of amino acid-level descriptors of protein structures and functions was substantially expanded since its release in 2020. This expansion includes substantial increase in the size, scope, and quality of the underlying data, the addition of experimental structural information, the inclusion of new data download options, and an upgraded graphical interface. DescribePROT currently covers 19 structural and functional descriptors for proteins in 273 reference proteomes generated by 11 accurate and complementary predictive tools. Users can search our resource in multiple ways, interact with the data using the graphical interface, and download data at various scales including individual proteins, entire proteomes, and whole database. The annotations in DescribePROT are useful for a broad spectrum of studies that include investigations of protein structure and function, development and validation of predictive tools, and to support efforts in understanding molecular underpinnings of diseases and development of therapeutics. DescribePROT can be freely accessed at http://biomine.cs.vcu.edu/servers/DESCRIBEPROT/.

DEPICTER2: a comprehensive webserver for intrinsic disorder and disorder function prediction.

Intrinsic disorder in proteins is relatively abundant in nature and essential for a broad spectrum of cellular functions. While disorder can be accurately predicted from protein sequences, as it was empirically demonstrated in recent community-organized assessments, it is rather challenging to collect and compile a comprehensive prediction that covers multiple disorder functions. To this end, we introduce the DEPICTER2 (DisorderEd PredictIon CenTER) webserver that offers convenient access to a curated collection of fast and accurate disorder and disorder function predictors. This server includes a state-of-the-art disorder predictor, flDPnn, and five modern methods that cover all currently predictable disorder functions: disordered linkers and protein, peptide, DNA, RNA and lipid binding. DEPICTER2 allows selection of any combination of the six methods, batch predictions of up to 25 proteins per request and provides interactive visualization of the resulting predictions. The webserver is freely available at http://biomine.cs.vcu.edu/servers/DEPICTER2/.

Real-time Observation of Macroscopic Helical Morphologies under Optical Microscope: A Curious Case of π-π Stacking Driven Molecular Self-assembly of an Organic Gelator Devoid of Hydrogen Bonding.

Supramolecular assemblies such as tubules/helix/double helix/helical tape etc. are usually submicron objects preventing direct observation under optical microscope. Chiral-pure form of these assemblies is important for potential applications. Herein, we report a rare phenomenon wherein a DMSO gel of a simple terpyridine derivative [(4-CNPhe)4PyTerp] produced macroscopic helical morphologies (µm length scale) which could be observed under optical microscope, formation of which could be monitored by optical videography, stable enough to withstand acidic vapour, robust enough to display reversible gel↔sol in response to acidic and ammonia vapour and sturdy enough to be maneuvered with a needle. These properties appeared to be unique to the title compound as the other related derivatives failed to display such assembly structures. SXRD and MD simulation studies suggested that weak interactions (π-π stacking) played a crucial role in the self-assembly process.

Conservation and coevolution determine evolvability of different classes of disordered residues in human intrinsically disordered proteins.

Structure, function, and evolution are interdependent properties of proteins. Diversity of protein functions arising from structural variations is a potential driving force behind protein evolvability. Intrinsically disordered proteins or regions (IDPs or IDRs) lack well-defined structure under normal physiological conditions, yet, they are highly functional. Increased occurrence of IDPs in eukaryotes compared to prokaryotes indicates strong correlation of protein evolution and disorderedness. IDPs generally have higher evolution rate compared to globular proteins. Structural pliability allows IDPs to accommodate multiple mutations without affecting their functional potential. Nevertheless, how evolutionary signals vary between different classes of disordered residues (DRs) in IDPs is poorly understood. This study addresses variation of evolutionary behavior in terms of residue conservation and intra-protein coevolution among structural and functional classes of DRs in IDPs. Analyses are performed on 579 human IDPs, which are classified based on length of IDRs, interacting partners and functional classes. We find short IDRs are less conserved than long IDRs or full IDPs. Functional classes which require flexibility and specificity to perform their activity comparatively evolve slower than others. Disorder promoting amino acids evolve faster than order promoting amino acids. Pro, Gly, Ile, and Phe have unique coevolving nature which further emphasizes on their roles in IDPs. This study sheds light on evolutionary footprints in different classes of DRs from human IDPs and enhances our understanding of the structural and functional potential of IDPs.

Unusual RNA binding of FUS RRM studied by molecular dynamics simulation and enhanced sampling method.

Amyotrophic lateral sclerosis (ALS) and frontotemporal lobe degeneration (FTLD) are two inter-related intractable diseases of motor neuron degeneration. Fused in sarcoma (FUS) is found in cytoplasmic accumulation of ALS and FTLD patients, which readily link the protein with the diseases. The RNA recognition motif (RRM) of FUS has the canonical α-ß folds along with an unusual lysine-rich loop (KK-loop) between α1 and ß2. This KK-loop is highly conserved among FET family proteins. Another contrasting feature of FUS RRM is the absence of critical binding residues, which are otherwise highly conserved in canonical RRMs. These residues in FUS RRM are Thr286, Glu336, Thr338, and Ser367, which are substitutions of lysine, phenylalanine, phenylalanine, and lysine, respectively, in other RRMs. Considering the importance of FUS in RNA regulation and metabolism, and its implication in ALS and FTLD, it is important to elucidate the underlying molecular mechanism of RNA recognition. In this study, we have performed molecular dynamics simulation with enhanced sampling to understand the conformational dynamics of noncanonical FUS RRM and its binding with RNA. We studied two sets of mutations: one with alanine mutation of KK-loop and another with KK-loop mutations along with critical binding residues mutated back to their canonical form. We find that concerted movement of KK-loop and loop between ß2 and ß3 facilitates the folding of the partner RNA, indicating an induced-fit mechanism of RNA binding. Flexibility of the RRM is highly restricted upon mutating the lysine residues of the KK-loop, resulting in weaker binding with the RNA. Our results also suggest that absence of the canonical residues in FUS RRM along with the KK-loop is equally important in regulating its binding dynamics. This study provides a significant structural insight into the binding of FUS RRM with its cognate RNA, which may further help in designing potential drugs targeting noncanonical RNA recognition.

Do sequence neighbours of intrinsically disordered regions promote structural flexibility in intrinsically disordered proteins?

Intrinsically disordered proteins (IDPs) are crucial players in various cellular activities. Several experimental and computational analyses have been conducted to study structural pliability and functional potential of IDPs. In spite of active research in past few decades, what induces structural disorder in IDPs and how is still elusive. Many studies testify that sequential and spatial neighbours often play important roles in determining structural and functional behaviour of proteins. Considering this fact, we assessed sequence neighbours of intrinsically disordered regions (IDRs) to understand if they have any role to play in inducing structural flexibility in IDPs. Our analysis includes 97% eukaryotic IDPs and 3% from bacteria and viruses. Physicochemical and structural parameters including amino acid propensity, hydrophobicity, secondary structure propensity, relative solvent accessibility, B-factor and atomic packing density are used to characterise the neighbouring residues of IDRs (NRIs). We show that NRIs exhibit a unique nature, which makes them stand out from both ordered and disordered residues. They show correlative occurrences of residue pairs like Ser-Thr and Gln-Asn, indicating their tendency to avoid strong biases of order or disorder promoting amino acids. We also find differential preferences of amino acids between N- and C-terminal neighbours, which might indicate a plausible directional effect on the dynamics of adjacent IDRs. We designed an efficient prediction tool using Random Forest to distinguish the NRIs from the ordered residues. Our findings will contribute to understand the behaviour of IDPs, and may provide potential lead in deciphering the role of IDRs in protein folding and assembly.

A structural perspective of RNA recognition by intrinsically disordered proteins.

Protein-RNA recognition is essential for gene expression and its regulation, which is indispensable for the survival of the living organism at one hand, on the other hand, misregulation of this recognition may lead to their extinction. Polymorphic conformation of both the interacting partners is a characteristic feature of such molecular recognition that promotes the assembly. Many RNA binding proteins (RBP) or regions in them are found to be intrinsically disordered, and this property helps them to play a central role in the regulatory processes. Sequence composition and the length of the flexible linkers between RNA binding domains in RBPs are crucial in making significant contacts with its partner RNA. Polymorphic conformations of RBPs can provide thermodynamic advantage to its binding partner while acting as a chaperone. Prolonged extensions of the disordered regions in RBPs also contribute to the stability of the large cellular machines including ribosome and viral assemblies. The involvement of these disordered regions in most of the significant cellular processes makes RBPs highly associated with various human diseases that arise due to their misregulation.

Taxonomy-specific assessment of intrinsic disorder predictions at residue and region levels in higher eukaryotes, protists, archaea, bacteria and viruses.

Intrinsic disorder predictors were evaluated in several studies including the two large CAID experiments. However, these studies are biased towards eukaryotic proteins and focus primarily on the residue-level predictions. We provide first-of-its-kind assessment that comprehensively covers the taxonomy and evaluates predictions at the residue and disordered region levels. We curate a benchmark dataset that uniformly covers eukaryotic, archaeal, bacterial, and viral proteins. We find that predictive performance differs substantially across taxonomy, where viruses are predicted most accurately, followed by protists and higher eukaryotes, while bacterial and archaeal proteins suffer lower levels of accuracy. These trends are consistent across predictors. We also find that current tools, except for flDPnn, struggle with reproducing native distributions of the numbers and sizes of the disordered regions. Moreover, analysis of two variants of disorder predictions derived from the AlphaFold2 predicted structures reveals that they produce accurate residue-level propensities for archaea, bacteria and protists. However, they underperform for higher eukaryotes and generally struggle to accurately identify disordered regions. Our results motivate development of new predictors that target bacteria and archaea and which produce accurate results at both residue and region levels. We also stress the need to include the region-level assessments in future assessments.

Hyperinsulinemic State and Hypokalemic Quadriparesis in Tropical Fever: Is There a Link?

It is rare for quadriparesis to manifest as a symptom of tropical illnesses. With a history of only one fever episode one week prior, our patient, a 48-year-old male with obesity and prediabetes, who was also known to have ankylosing spondylitis, presented with acute onset flaccid quadriparesis. He did not exhibit any additional symptoms of dengue, such as bleeding tendencies, petechial rashes, thrombocytopenia, or febrile episodes. Upon examination, it was discovered that he had extremely low serum potassium levels and was dengue non-specific antigen 1 (NS1) positive. His hyperinsulinemia, as seen by elevated C peptide levels, most likely caused a transcellular shift that was then triggered by the dengue infection, leading to hypokalemic paralysis.

An international prospective study of INICC analyzing the incidence and risk factors for catheter-associated urinary tract infections in 235 ICUs across 8 Asian Countries.

BACKGROUND: Identify urinary catheter (UC)-associated urinary tract infections (CAUTI) incidence and risk factors (RF) in 235 ICUs in 8 Asian countries: India, Malaysia, Mongolia, Nepal, Pakistan, the Philippines, Thailand, and Vietnam. METHODS: From January 1, 2014, to February 12, 2022, we conducted a prospective cohort study. To estimate CAUTI incidence, the number of UC days was the denominator, and CAUTI was the numerator. To estimate CAUTI RFs, we analyzed 11 variables using multiple logistic regression. RESULTS: 84,920 patients hospitalized for 499,272 patient days acquired 869 CAUTIs. The pooled CAUTI rate per 1,000 UC-days was 3.08; for those using suprapubic-catheters (4.11); indwelling-catheters (2.65); trauma-ICU (10.55), neurologic-ICU (7.17), neurosurgical-ICU (5.28); in lower-middle-income countries (3.05); in upper-middle-income countries (1.71); at public-hospitals (5.98), at private-hospitals (3.09), at teaching-hospitals (2.04). The following variables were identified as CAUTI RFs: Age (adjusted odds ratio [aOR] = 1.01; 95% CI = 1.01-1.02; P < .0001); female sex (aOR = 1.39; 95% CI = 1.21-1.59; P < .0001); using suprapubic-catheter (aOR = 4.72; 95% CI = 1.69-13.21; P < .0001); length of stay before CAUTI acquisition (aOR = 1.04; 95% CI = 1.04-1.05; P < .0001); UC and device utilization-ratio (aOR = 1.07; 95% CI = 1.01-1.13; P = .02); hospitalized at trauma-ICU (aOR = 14.12; 95% CI = 4.68-42.67; P < .0001), neurologic-ICU (aOR = 14.13; 95% CI = 6.63-30.11; P < .0001), neurosurgical-ICU (aOR = 13.79; 95% CI = 6.88-27.64; P < .0001); public-facilities (aOR = 3.23; 95% CI = 2.34-4.46; P < .0001). DISCUSSION: CAUTI rate and risk are higher for older patients, women, hospitalized at trauma-ICU, neurologic-ICU, neurosurgical-ICU, and public facilities. All of them are unlikely to change. CONCLUSIONS: It is suggested to focus on reducing the length of stay and the Urinary catheter device utilization ratio, avoiding suprapubic catheters, and implementing evidence-based CAUTI prevention recommendations.

Incidence and risk factors for catheter-associated urinary tract infection in 623 intensive care units throughout 37 Asian, African, Eastern European, Latin American, and Middle Eastern nations: A multinational prospective research of INICC.

OBJECTIVE: To identify urinary catheter (UC)-associated urinary tract infection (CAUTI) incidence and risk factors. DESIGN: A prospective cohort study. SETTING: The study was conducted across 623 ICUs of 224 hospitals in 114 cities in 37 African, Asian, Eastern European, Latin American, and Middle Eastern countries. PARTICIPANTS: The study included 169,036 patients, hospitalized for 1,166,593 patient days. METHODS: Data collection took place from January 1, 2014, to February 12, 2022. We identified CAUTI rates per 1,000 UC days and UC device utilization (DU) ratios stratified by country, by ICU type, by facility ownership type, by World Bank country classification by income level, and by UC type. To estimate CAUTI risk factors, we analyzed 11 variables using multiple logistic regression. RESULTS: Participant patients acquired 2,010 CAUTIs. The pooled CAUTI rate was 2.83 per 1,000 UC days. The highest CAUTI rate was associated with the use of suprapubic catheters (3.93 CAUTIs per 1,000 UC days); with patients hospitalized in Eastern Europe (14.03) and in Asia (6.28); with patients hospitalized in trauma (7.97), neurologic (6.28), and neurosurgical ICUs (4.95); with patients hospitalized in lower-middle-income countries (3.05); and with patients in public hospitals (5.89).The following variables were independently associated with CAUTI: Age (adjusted odds ratio [aOR], 1.01; P < .0001), female sex (aOR, 1.39; P < .0001), length of stay (LOS) before CAUTI-acquisition (aOR, 1.05; P < .0001), UC DU ratio (aOR, 1.09; P < .0001), public facilities (aOR, 2.24; P < .0001), and neurologic ICUs (aOR, 11.49; P < .0001). CONCLUSIONS: CAUTI rates are higher in patients with suprapubic catheters, in middle-income countries, in public hospitals, in trauma and neurologic ICUs, and in Eastern European and Asian facilities.Based on findings regarding risk factors for CAUTI, focus on reducing LOS and UC utilization is warranted, as well as implementing evidence-based CAUTI-prevention recommendations.

Computational prediction of disordered binding regions.

One of the key features of intrinsically disordered regions (IDRs) is their ability to interact with a broad range of partner molecules. Multiple types of interacting IDRs were identified including molecular recognition fragments (MoRFs), short linear sequence motifs (SLiMs), and protein-, nucleic acids- and lipid-binding regions. Prediction of binding IDRs in protein sequences is gaining momentum in recent years. We survey 38 predictors of binding IDRs that target interactions with a diverse set of partners, such as peptides, proteins, RNA, DNA and lipids. We offer a historical perspective and highlight key events that fueled efforts to develop these methods. These tools rely on a diverse range of predictive architectures that include scoring functions, regular expressions, traditional and deep machine learning and meta-models. Recent efforts focus on the development of deep neural network-based architectures and extending coverage to RNA, DNA and lipid-binding IDRs. We analyze availability of these methods and show that providing implementations and webservers results in much higher rates of citations/use. We also make several recommendations to take advantage of modern deep network architectures, develop tools that bundle predictions of multiple and different types of binding IDRs, and work on algorithms that model structures of the resulting complexes.

CoMemMoRFPred: Sequence-based Prediction of MemMoRFs by Combining Predictors of Intrinsic Disorder, MoRFs and Disordered Lipid-binding Regions.

Molecular recognition features (MoRFs) are a commonly occurring type of intrinsically disordered regions (IDRs) that undergo disorder-to-order transition upon binding to partner molecules. We focus on recently characterized and functionally important membrane-binding MoRFs (MemMoRFs). Motivated by the lack of computational tools that predict MemMoRFs, we use a dataset of experimentally annotated MemMoRFs to conceptualize, design, evaluate and release an accurate sequence-based predictor. We rely on state-of-the-art tools that predict residues that possess key characteristics of MemMoRFs, such as intrinsic disorder, disorder-to-order transition and lipid-binding. We identify and combine results from three tools that include flDPnn for the disorder prediction, DisoLipPred for the prediction of disordered lipid-binding regions, and MoRFCHiBiLight for the prediction of disorder-to-order transitioning protein binding regions. Our empirical analysis demonstrates that combining results produced by these three methods generates accurate predictions of MemMoRFs. We also show that use of a smoothing operator produces predictions that closely mimic the number and sizes of the native MemMoRF regions. The resulting CoMemMoRFPred method is available as an easy-to-use webserver at http://biomine.cs.vcu.edu/servers/CoMemMoRFPred. This tool will aid future studies of MemMoRFs in the context of exploring their abundance, cellular functions, and roles in pathologic phenomena.

qNABpredict: Quick, accurate, and taxonomy-aware sequence-based prediction of content of nucleic acid binding amino acids.

Protein sequence-based predictors of nucleic acid (NA)-binding include methods that predict NA-binding proteins and NA-binding residues. The residue-level tools produce more details but suffer high computational cost since they must predict every amino acid in the input sequence and rely on multiple sequence alignments. We propose an alternative approach that predicts content (fraction) of the NA-binding residues, offering more information than the protein-level prediction and much shorter runtime than the residue-level tools. Our first-of-its-kind content predictor, qNABpredict, relies on a small, rationally designed and fast-to-compute feature set that represents relevant characteristics extracted from the input sequence and a well-parametrized support vector regression model. We provide two versions of qNABpredict, a taxonomy-agnostic model that can be used for proteins of unknown taxonomic origin and more accurate taxonomy-aware models that are tailored to specific taxonomic kingdoms: archaea, bacteria, eukaryota, and viruses. Empirical tests on a low-similarity test dataset show that qNABpredict is 100 times faster and generates statistically more accurate content predictions when compared to the content extracted from results produced by the residue-level predictors. We also show that qNABpredict's content predictions can be used to improve results generated by the residue-level predictors. We release qNABpredict as a convenient webserver and source code at http://biomine.cs.vcu.edu/servers/qNABpredict/. This new tool should be particularly useful to predict details of protein-NA interactions for large protein families and proteomes.

Treatment Outcome with High versus low-to-moderate Dosing of Corticosteroids in Early vis-a-vis Late-onset Hypoxic Cases of COVID-19: A Multicentric Retrospective Cohort Study.

Background: Corticosteroid dosing in COVID-19 cases associated with early-onset and late-onset hypoxia have not been separately explored. Methods: In this retrospective cohort study, we divided hypoxic COVID-19 cases into groups based on timing of initiation of corticosteroids relative to onset of symptoms; Group A (≤6th day), Group B (7th-9th day) and Group C (≥10th day), each group being sub-grouped into high and low-to-moderate dose corticosteroid recipients. Cox regression with propensity scoring was used to compare 28-day mortality between high and low-to-moderate dose recipients separately in Group A, Group B, Group C. Results: Among 505 patients included, propensity score matched Cox regression showed greater risk of all-cause mortality among high dose recipients in Group A [HR= 7.35, 95%CI 3.36-16.11, p-value<0·01, N=114] and Group B [HR=3.17, 95%CI 1.65-6.07, p-value<0·01, N=251]. In Group C, mortality was lowest [12.8% (18/140)] with no significant difference between sub-groups [HR=2.52, 95%CI 0.22-29.15, p-value=0.459, N=140]. Kruskal-Wallis Test between Group A, Group B and Group C for six pre-defined exposure variables showed significant differences for Neutrophil:Lymphocyte Ratio (NLR). Conclusion: When steroids were initiated early (owing to an earlier onset of hypoxic symptoms), a high dose of corticosteroid was associated with greater overall 28-day mortality compared to a low-to-moderate dose. NLR, a marker for individual immune response, varied between treatment groups.

Impaired nuclear transport induced by juvenile ALS causing P525L mutation in NLS domain of FUS: A molecular mechanistic study.

Amyotrophic lateral sclerosis (ALS) and fronto-temporal lobar degeneration (FTLD) are progressive neurological disorders affecting motor neurons. Cellular aggregates of fused in sarcoma (FUS) protein are found in cytoplasm of ALS and FTLD patients. Nuclear localisation signal (NLS) domain of FUS binds to Karyopherin ß2 (Kapß2), which drives nuclear transport of FUS from cytoplasm. Several pathogenic mutations are reported in FUS NLS, which are associated with its impaired nuclear transport and cytoplasmic mis-localisation. P525L mutation in NLS is most commonly found in cases of juvenile ALS (jALS), which affects individuals below 25 years of age. jALS progresses aggressively causing death within a year of its onset. This study elucidates the molecular mechanism behind jALS-causing P525L mutation hindering nuclear transport of FUS. We perform multiple molecular dynamics simulations in aqueous and hydrophobic solvent to understand the effect of the mutation at molecular level. Dynamics of Kapß2-FUS complex is better captured in hydrophobic solvent compared to aqueous solvent. P525 and Y526 (PY-motif) of NLS exhibit fine-tuned stereochemical arrangement, which is essential for optimum Kapß2 binding. P525L causes loss of several native contacts at interface leading to weaker binding, which promotes self-aggregation of FUS in cytoplasm. Native complex samples closed conformation, while mutant complex exhibits open conformation exposing hydrophilic residues of Kapß2 to hydrophobic solvent. Mutant complex also fails to exhibit spring-like motion essential for its transport through nuclear pore complex. This study provides a mechanistic insight of binding affinity between NLS and Kapß2 that inhibits self-aggregation of FUS preventing the disease condition.

Molecular mechanism of the enhanced viral fitness contributed by secondary mutations in the hemagglutinin protein of oseltamivir resistant H1N1 influenza viruses: modeling studies of antibody and receptor binding.

The envelope protein hemagglutinin (HA) of influenza viruses is primarily associated with host antibody and receptor interactions. The HA protein is known to maintain a functional balance with neuraminidase (NA), the other major envelope protein. Prior to 2007-2008, human seasonal H1N1 viruses possessing the NA H274Y mutation, which confers oseltamivir resistance, generally had low growth capability. Subsequently, secondary mutations that compensate for the deleterious effect of the NA H274Y mutation have been identified. The molecular mechanism of how the defect could be counteracted by these secondary mutations is not fully understood. We studied here the effect of three such mutations (T86K, K144E and R192K) in the HA protein, which are located at either the HA receptor binding site or in the H1N1 antigenic sites. Molecular docking and dynamics studies showed that, of the three mutations, the R192K mutation could have mediated neutralizing antibody escape and decreased receptor binding affinity, either or both of which may have contributed to increased viral fitness. The study suggests the molecular basis of enhanced viral fitness induced by secondary mutations in the evolution of oseltamivir-resistant influenza strains.