Distinct localization of chiral proofreaders resolves organellar translation conflict in plants.

Plants have two endosymbiotic organelles originated from two bacterial ancestors. The transition from an independent bacterium to a successful organelle would have required extensive rewiring of biochemical networks for its integration with archaeal host. Here, using Arabidopsis as a model system, we show that plant D-aminoacyl-tRNA deacylase 1 (DTD1), of bacterial origin, is detrimental to organellar protein synthesis owing to its changed tRNA recognition code. Plants survive this conflict by spatially restricting the conflicted DTD1 to the cytosol. In addition, plants have targeted archaeal DTD2 to both the organelles as it is compatible with their translation machinery due to its strict D-chiral specificity and lack of tRNA determinants. Intriguingly, plants have confined bacterial-derived DTD1 to work in archaeal-derived cytosolic compartment whereas archaeal DTD2 is targeted to bacterial-derived organelles. Overall, the study provides a remarkable example of the criticality of optimization of biochemical networks for survival and evolution of plant mitochondria and chloroplast.

On and off controls within dynein-dynactin on native cargoes.

The dynein-dynactin nanomachine transports cargoes along microtubules in cells. Why dynactin interacts separately with the dynein motor and also with microtubules is hotly debated. Here we disrupted these interactions in a targeted manner on phagosomes extracted from cells, followed by optical trapping to interrogate native dynein-dynactin teams on single phagosomes. Perturbing the dynactin-dynein interaction reduced dynein's on rate to microtubules. In contrast, perturbing the dynactin-microtubule interaction increased dynein's off rate markedly when dynein was generating force against the optical trap. The dynactin-microtubule link is therefore required for persistence against load, a finding of importance because disease-relevant mutations in dynein-dynactin are known to interfere with "high-load" functions of dynein in cells. Our findings call attention to a less studied property of dynein-dynactin, namely, its detachment against load, in understanding dynein dysfunction.

Stone mining work and dust pollution in Birbhum district, West Bengal, India.

Dust pollution is common in Indian roads and several industrial settings (including mines) that affects human health. Identification and characterization of the dust particles in the mining area is essential for knowing the properties of the dust that effectively causes ailments to humans, particularly among workers those who are working in unorganized industrial settings. The present study aimed to determine the level of dust pollution and to know the size and characterize the dust particles in the Pachami-Hatgacha stone mine areas of Birbhum district, West Bengal, India. Dust samples were collected and analysed for Dynamic Light Scattering (DLS) to determine the size and shape of the particles, Fourier Transform Infrared Spectroscopy (FT-IR) to determine the free silica content, and X-ray Florence (XRF) analysis for quantitative estimation of components in the sample. All the analyses were done following standard instrumentation and techniques. The size of the dust particles was much less (ranges 101-298 nm) than the size of respirable particles (2500 nm). Those were mostly generated as well as precipitated during peak working hours of the day. Presence of considerable amounts of silica was confirmed by the FT-IR (strong and broad band at 1000 cm-1) and XRF analysis (76.85% SiO2). Exposure to these dust particles may cause severe health impairments. Therefore, interventions like wet drilling and blasting, sprinkling of water during peak working hours, and awareness of use of personal protective devices among workers are required to reduce the risk and hazards associated with dust pollution to the health of miners and inhabitants around the mines.

A knowledge-based scoring function to assess quaternary associations of proteins.

MOTIVATION: The elucidation of all inter-protein interactions would significantly enhance our knowledge of cellular processes at a molecular level. Given the enormity of the problem, the expenses and limitations of experimental methods, it is imperative that this problem is tackled computationally. In silico predictions of protein interactions entail sampling different conformations of the purported complex and then scoring these to assess for interaction viability. In this study, we have devised a new scheme for scoring protein-protein interactions. RESULTS: Our method, PIZSA (Protein Interaction Z-Score Assessment), is a binary classification scheme for identification of native protein quaternary assemblies (binders/nonbinders) based on statistical potentials. The scoring scheme incorporates residue-residue contact preference on the interface with per residue-pair atomic contributions and accounts for clashes. PIZSA can accurately discriminate between native and non-native structural conformations from protein docking experiments and outperform other contact-based potential scoring functions. The method has been extensively benchmarked and is among the top 6 methods, outperforming 31 other statistical, physics based and machine learning scoring schemes. The PIZSA potentials can also distinguish crystallization artifacts from biological interactions. AVAILABILITY AND IMPLEMENTATION: PIZSA is implemented as a web server at http://cospi.iiserpune.ac.in/pizsa and can be downloaded as a standalone package from http://cospi.iiserpune.ac.in/pizsa/Download/Download.html. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Protein Interaction Z Score Assessment (PIZSA): an empirical scoring scheme for evaluation of protein-protein interactions.

Our web server, PIZSA (http://cospi.iiserpune.ac.in/pizsa), assesses the likelihood of protein-protein interactions by assigning a Z Score computed from interface residue contacts. Our score takes into account the optimal number of atoms that mediate the interaction between pairs of residues and whether these contacts emanate from the main chain or side chain. We tested the score on 174 native interactions for which 100 decoys each were constructed using ZDOCK. The native structure scored better than any of the decoys in 146 cases and was able to rank within the 95th percentile in 162 cases. This easily outperforms a competing method, CIPS. We also benchmarked our scoring scheme on 15 targets from the CAPRI dataset and found that our method had results comparable to that of CIPS. Further, our method is able to analyse higher order protein complexes without the need to explicitly identify chains as receptors or ligands. The PIZSA server is easy to use and could be used to score any input three-dimensional structure and provide a residue pair-wise break up of the results. Attractively, our server offers a platform for users to upload their own potentials and could serve as an ideal testing ground for this class of scoring schemes.

In silico methods for design of biological therapeutics.

It has been twenty years since the first rationally designed small molecule drug was introduced into the market. Since then, we have progressed from designing small molecules to designing biotherapeutics. This class of therapeutics includes designed proteins, peptides and nucleic acids that could more effectively combat drug resistance and even act in cases where the disease is caused because of a molecular deficiency. Computational methods are crucial in this design exercise and this review discusses the various elements of designing biotherapeutic proteins and peptides. Many of the techniques discussed here, such as the deterministic and stochastic design methods, are generally used in protein design. We have devoted special attention to the design of antibodies and vaccines. In addition to the methods for designing these molecules, we have included a comprehensive list of all biotherapeutics approved for clinical use. Also included is an overview of methods that predict the binding affinity, cell penetration ability, half-life, solubility, immunogenicity and toxicity of the designed therapeutics. Biotherapeutics are only going to grow in clinical importance and are set to herald a new generation of disease management and cure.

Molecular dynamics simulations of displacement cascades in LiAlO2 and LiAl5O8 ceramics.

Molecular dynamics was employed to investigate the radiation damage due to collision cascades in LiAlO2 and LiAl5O8, the latter being a secondary phase formed in the former during irradiation. Atomic displacement cascades were simulated by initiating primary knock-on atoms (PKA) with energy values = 5, 10 and 15 keV and the damage was quantified by the number of Frenkel pairs formed for each species: Li, Al and O. The primary challenges of modeling an ionic system with and without a core-shell model for oxygen atoms were addressed and new findings on the radiation resistance of these ceramics are presented. The working of a variable timestep function and the kinetics in the background of the simulations have been elaborated to highlight the novelty of the simulation approach. More importantly, the key results indicated that LiAlO2 experiences much more radiation damage than LiAl5O8, where the number of Li Frenkel pairs in LiAlO2 was 3-5 times higher than in LiAl5O8 while the number of Frenkel pairs for Al and O in LiAlO2 are ~ 2 times higher than in LiAl5O8. The primary reason is high displacement threshold energies (Ed) in LiAl5O8 for Li cations. The greater Ed for Li imparts higher resistance to damage during the collision cascade and thus inhibits amorphization in LiAl5O8. The presented results suggest that LiAl5O8 is likely to maintain structural integrity better than LiAlO2 in the irradiation conditions studied in this work.

Determination and speciation of arsenic in drinking water samples by X-ray spectrometry technique.

Arsenic is ranked as the first compound in the Substance Priority List 2023 by the Agency for Toxic Substances and Disease Registry (ATSDR). The most prominent entrance to the human body is through drinking water wherein the predominant species are arsenite and arsenate. The more toxic As(III) has rigorously threatened human health worldwide; hence, speciation and separation are the need of the hour. In this article, we have reported a simple method of arsenic speciation by wavelength dispersive X-ray fluorescence (WD-XRF) spectrometer. Valence to core (VtC) electronic transitions, i.e., AsKß2,5 fluorescence lines were used for arsenic speciation. This speciation study by WD-XRF entails direct measurement of activated alumina pellets containing arsenate and arsenite species adsorbed from water sample without separation of the trivalent and pentavalent species. This is the first report wherein the X-ray technique has been explored for speciation analysis of arsenic and the biggest advantage of the method lies in its applicability to direct analysis of synthesized nanotubes or other solid-phase extraction sorbents entrapping both the arsenic species. For determination of total arsenic using activated alumina as adsorbent, the most intense AsKα1,2 analytical lines were used and the instrumental limit of detection and the lower limit of quantification were 0.23 µg/L and 0.89 µg/L, respectively. For speciation, these limits were calculated to be 50 µg/L and 200 µg/L, respectively.

A translation proofreader of archaeal origin imparts multi-aldehyde stress tolerance to land plants.

Aldehydes, being an integral part of carbon metabolism, energy generation, and signalling pathways, are ingrained in plant physiology. Land plants have developed intricate metabolic pathways which involve production of reactive aldehydes and its detoxification to survive harsh terrestrial environments. Here, we show that physiologically produced aldehydes, i.e., formaldehyde and methylglyoxal in addition to acetaldehyde, generate adducts with aminoacyl-tRNAs, a substrate for protein synthesis. Plants are unique in possessing two distinct chiral proofreading systems, D-aminoacyl-tRNA deacylase1 (DTD1) and DTD2, of bacterial and archaeal origins, respectively. Extensive biochemical analysis revealed that only archaeal DTD2 can remove the stable D-aminoacyl adducts on tRNA thereby shielding archaea and plants from these system-generated aldehydes. Using Arabidopsis as a model system, we have shown that the loss of DTD2 gene renders plants susceptible to these toxic aldehydes as they generate stable alkyl modification on D-aminoacyl-tRNAs, which are recycled only by DTD2. Bioinformatic analysis identifies the expansion of aldehyde metabolising repertoire in land plant ancestors which strongly correlates with the recruitment of archaeal DTD2. Finally, we demonstrate that the overexpression of DTD2 offers better protection against aldehydes than in wild type Arabidopsis highlighting its role as a multi-aldehyde detoxifier that can be explored as a transgenic crop development strategy.

Rapid method of arsenic estimation in geological samples by WD-XRF using a novel concept of As-Pb concentration equivalence.

The presence of arsenic in ground waters of many countries has been a subject of global concern due to its toxicity. Primary sources of arsenic are geogenic, i.e. weathering and erosion of rocks and soils containing arsenic. This paper presents a rapid method for determination of arsenic in solid geological samples by wavelength dispersive X-ray fluorescence spectrometer. To achieve the best LLD (lower limit of detection), the most intense X-ray fluorescence line Kα1,2 is preferably used for determination of elemental concentrations because it pertains to the most probable transition. But the greatest challenge in arsenic estimation is the serious line overlap of AsKα1,2 lines with the equi-energy PbLα1,2 lines. By using the conventional line overlap correction methods, uncertainty and detection limits in arsenic determination are degraded to an unacceptable degree in samples which contains high lead and low arsenic concentrations. The proposed method bypasses the line overlap issue in employing a novel concept of arsenic-lead concentration equivalence factor for the cumulative peak of AsKα1,2 and PbLα1,2 fluorescence lines. The constancy of this factor for all geological matrices facilitates arsenic determination in samples universally irrespective of matrix elements. For the method validation, 22 international certified reference materials have been analysed and the results proved to be propitious wherein only one value out of 22 determinations showed relative error more than 20% of the certified values. This attests to the high accuracy of the proposed method which can effectively determine arsenic below 5 mg/kg in the presence of high lead concentration up to 1000 mg/kg.

Molecular mechanisms of inorganic-phosphate release from the core and barbed end of actin filaments.

The release of inorganic phosphate (Pi) from actin filaments constitutes a key step in their regulated turnover, which is fundamental to many cellular functions. The mechanisms underlying Pi release from the core and barbed end of actin filaments remain unclear. Here, using human and bovine actin isoforms, we combine cryo-EM with molecular-dynamics simulations and in vitro reconstitution to demonstrate how actin releases Pi through a 'molecular backdoor'. While constantly open at the barbed end, the backdoor is predominantly closed in filament-core subunits and opens only transiently through concerted amino acid rearrangements. This explains why Pi escapes rapidly from the filament end but slowly from internal subunits. In a nemaline-myopathy-associated actin variant, the backdoor is predominantly open in filament-core subunits, resulting in accelerated Pi release and filaments with drastically shortened ADP-Pi caps. Our results provide the molecular basis for Pi release from actin and exemplify how a disease-linked mutation distorts the nucleotide-state distribution and atomic structure of the filament.

Spatial information transfer in hippocampal place cells depends on trial-to-trial variability, symmetry of place-field firing, and biophysical heterogeneities.

The relationship between the feature-tuning curve and information transfer profile of individual neurons provides vital insights about neural encoding. However, the relationship between the spatial tuning curve and spatial information transfer of hippocampal place cells remains unexplored. Here, employing a stochastic search procedure spanning thousands of models, we arrived at 127 conductance-based place-cell models that exhibited signature electrophysiological characteristics and sharp spatial tuning, with parametric values that exhibited neither clustering nor strong pairwise correlations. We introduced trial-to-trial variability in responses and computed model tuning curves and information transfer profiles, using stimulus-specific (SSI) and mutual (MI) information metrics, across locations within the place field. We found spatial information transfer to be heterogeneous across models, but to reduce consistently with increasing levels of variability. Importantly, whereas reliable low-variability responses implied that maximal information transfer occurred at high-slope regions of the tuning curve, increase in variability resulted in maximal transfer occurring at the peak-firing location in a subset of models. Moreover, experience-dependent asymmetry in place-field firing introduced asymmetries in the information transfer computed through MI, but not SSI, and the impact of activity-dependent variability on information transfer was minimal compared to activity-independent variability. We unveiled ion-channel degeneracy in the regulation of spatial information transfer, and demonstrated critical roles for N-methyl-d-aspartate receptors, transient potassium and dendritic sodium channels in regulating information transfer. Our results demonstrate that trial-to-trial variability, tuning-curve shape and biological heterogeneities critically regulate the relationship between the spatial tuning curve and spatial information transfer in hippocampal place cells.

Recruitment of archaeal DTD is a key event toward the emergence of land plants.

Streptophyte algae emerged as a land plant with adaptations that eventually led to terrestrialization. Land plants encounter a range of biotic and abiotic stresses that elicit anaerobic stress responses. Here, we show that acetaldehyde, a toxic metabolite of anaerobic stress, targets and generates ethyl adducts on aminoacyl-tRNA, a central component of the translation machinery. However, elongation factor thermo unstable (EF-Tu) safeguards l-aminoacyl-tRNA, but not d-aminoacyl-tRNA, from being modified by acetaldehyde. We identified a unique activity of archaeal-derived chiral proofreading module, d-aminoacyl-tRNA deacylase 2 (DTD2), that removes N-ethyl adducts formed on d-aminoacyl-tRNAs (NEDATs). Thus, the study provides the molecular basis of ethanol and acetaldehyde hypersensitivity in DTD2 knockout plants. We uncovered an important gene transfer event from methanogenic archaea to the ancestor of land plants. While missing in other algal lineages, DTD2 is conserved from streptophyte algae to land plants, suggesting its role toward the emergence and evolution of land plants.

Revisiting the supplementary relationship of dynamic contact angles measured by sessile-droplet and captive-bubble methods: Role of surface roughness.

HYPOTHESIS: Quantitative characterization of surface wettability through contact angle (CA) measurement using the sessile droplet (SD) or captive bubble (CB) methods is often limited by the intrinsic wetting properties of the substrate. Situations may arise when an extreme surface wettability may preclude using one of the two methods for predicting the behaviors of droplets or bubbles on the surface. This warrants a relationship between the dynamic CAs measured via the SD and CB methods. While the two dynamic CAs (e.g., the advancing CA of SD and receding CA of CB) add up to 180° on a smooth surface, the simple geometric supplementary principle may not apply for rough surfaces. EXPERIMENTS: We perform a systematic wettability characterization of solid substrates with varying degrees of roughness using the sessile-droplet and captive-bubble methods, and interpret the experimental observations using a theoretical model. FINDINGS: The dynamic contact angles measured by the sessile-droplet and captive-bubble methods deviate from the supplementary principle as the surface roughness is increased. We present a theoretical explanation for this disparity and predict the values of the contact angles using prevalent thermodynamic models of wetting and contact-angle hysteresis on rough substrates. The theoretical prediction is in good agreement with the experimental observations.

Machine learning assisted prediction of the Young's modulus of compositionally complex alloys.

We identify compositionally complex alloys (CCAs) that offer exceptional mechanical properties for elevated temperature applications by employing machine learning (ML) in conjunction with rapid synthesis and testing of alloys for validation to accelerate alloy design. The advantages of this approach are scalability, rapidity, and reasonably accurate predictions. ML tools were implemented to predict Young's modulus of refractory-based CCAs by employing different ML models. Our results, in conjunction with experimental validation, suggest that average valence electron concentration, the difference in atomic radius, a geometrical parameter λ and melting temperature of the alloys are the key features that determine the Young's modulus of CCAs and refractory-based CCAs. The Gradient Boosting model provided the best predictive capabilities (mean absolute error of 6.15 GPa) among the models studied. Our approach integrates high-quality validation data from experiments, literature data for training machine-learning models, and feature selection based on physical insights. It opens a new avenue to optimize the desired materials property for different engineering applications.

Structural insights of a cellobiose dehydrogenase enzyme from the basidiomycetes fungus Termitomyces clypeatus.

Filamentous fungi secrete various oxidative enzymes to degrade the glycosidic bonds of polysaccharides. Cellobiose dehydrogenase (CDH) (E.C.1.1.99.18) is one of the important lignocellulose degrading enzymes produced by various filamentous fungi. It contains two stereo specific ligand binding domains, cytochrome and dehydrogenase - one for heme and the other for flavin adenine dinucleotide (FAD) respectively. The enzyme is of commercial importance for its use in amperometric biosensor, biofuel production, lactose determination in food, bioremediation etc. Termitomyces clypeatus, an edible fungus belonging to the basidiomycetes group, is a good producer of CDH. In this paper we have analyzed the structural properties of this enzyme from T. clypeatus and identified a distinct carbohydrate binding module (CBM) which is not present in most fungi belonging to the basidiomycetes group. In addition, the dehydrogenase domain of T. clypeatus CDH exhibited the absence of cellulose binding residues which is in contrast to the dehydrogenase domains of CDH of other basidiomycetes. Sequence analysis of cytochrome domain showed that the important residues of this domain were conserved like in other fungal CDHs. Phylogenetic tree, constructed using basidiomycetes and ascomycetes CDH sequences, has shown that very surprisingly the CDH from T. clypeatus, which is classified as a basidiomycetes fungus, is clustered with the ascomycetes group. A homology model of this protein has been constructed using the CDH enzyme of ascomycetes fungus Myricoccum thermophilum as a template since it has been found to be the best match sequence with T. clypeatus CDH. We also have modelled the protein with its substrate, cellobiose, which has helped us to identify the substrate interacting residues (L354, P606, T629, R631, Y649, N732, H733 and N781) localized within its dehydrogenase domain. Our computational investigation revealed for the first time the presence of all three domains - cytochrome, dehydrogenase and CBM - in the CDH of T. clypeatus, a basidiomycetes fungus. In addition to discovering the unique structural attributes of this enzyme from T. clypeatus, our study also discusses the possible phylogenetic status of this fungus.

Predicting and designing therapeutics against the Nipah virus.

Despite Nipah virus outbreaks having high mortality rates (>70% in Southeast Asia), there are no licensed drugs against it. In this study, we have considered all 9 Nipah proteins as potential therapeutic targets and computationally identified 4 putative peptide inhibitors (against G, F and M proteins) and 146 small molecule inhibitors (against F, G, M, N, and P proteins). The computations include extensive homology/ab initio modeling, peptide design and small molecule docking. An important contribution of this study is the increased structural characterization of Nipah proteins by approximately 90% of what is deposited in the PDB. In addition, we have carried out molecular dynamics simulations on all the designed protein-peptide complexes and on 13 of the top shortlisted small molecule ligands to check for stability and to estimate binding strengths. Details, including atomic coordinates of all the proteins and their ligand bound complexes, can be accessed at http://cospi.iiserpune.ac.in/Nipah. Our strategy was to tackle the development of therapeutics on a proteome wide scale and the lead compounds identified could be attractive starting points for drug development. To counter the threat of drug resistance, we have analysed the sequences of the viral strains from different outbreaks, to check whether they would be sensitive to the binding of the proposed inhibitors.