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Abstract Direct exposure to the fungal species Alternaria alternata is a major risk factor for the development of asthma, allergic rhinitis, and inflammation. As of November 23rd 2020, the NCBI protein database showed 11,227 proteins from A. alternata genome as hypothetical proteins (HPs). Allergens are the main causative of several life-threatening diseases, especially in fungal infections. Therefore, the main aim of the study is to identify the potentially allergenic inducible proteins from the HPs in A. alternata and their associated functional assignment for the complete understanding of the complex biological systems at the molecular level. AlgPred and Structural Database of Allergenic Proteins (SDAP) were used for the prediction of potential allergens from the HPs of A. alternata. While analyzing the proteome data, 29 potential allergens were predicted by AlgPred and further screening in SDAP confirmed the allergic response of 10 proteins. Extensive bioinformatics tools including protein family classification, sequence-function relationship, protein motif discovery, pathway interactions, and intrinsic features from the amino acid sequence were used to successfully predict the probable functions of the 10 HPs. The functions of the HPs are characterized as chitin-binding, ribosomal protein P1, thaumatin, glycosyl hydrolase, and NOB1 proteins. The subcellular localization and signal peptide prediction of these 10 proteins has further provided additional information on localization and function. The allergens prediction and functional annotation of the 10 proteins may facilitate a better understanding of the allergenic mechanism of A. alternata in asthma and other diseases. The functional domain level insights and predicted structural features of the allergenic proteins help to understand the pathogenesis and host immune tolerance. The outcomes of the study would aid in the development of specific drugs to combat A. alternata infections.

Background: Carbapenem-resistant Acinetobacter baumannii is an opportunistic pathogen responsible for nosocomial infections and is one of the biggest global threats according to the World Health Organization (WHO), particularly causing substantial morbidity and mortality.Objectives: This study aimed at using computational approaches to screen meropenem and its analogs against OXA-23-positive Acinetobacter baumannii, analyzing the correlations between kinetic and phenotypic characteristics.Methods: A total of 5,450 compounds were screened using virtual screening workflow (HTVS, Glide-SP, and Glide-XP) to identify the best compounds based on their binding energy and interactions against OXA-23 and OXA-27 as they had phenotypic data available. Molecular dynamics simulation and density functional theory (DFT) studies were performed from the outcome of molecular docking analysis.Results: During simulations, meropenem and its analogs exhibited high-level stable interactions with Ser79, Ser126, Thr217, Trp219, and Arg259 of OXA-23. Meropenem displayed a CovDock energy of about −3.5 and −1.9 kcal mol-1 against OXA-23 and OXA-27, respectively. Among the 5,450 compounds, Pubchem_10645796, Pubchem_25224737, and ChEMBL_14 recorded CovDock energy between −6.0 and −9.0 kcal mol-1. Moreover, the infra-red (IR) spectrophotometric analysis revealed C=O and C-N atoms showing bands at 1,800 and 1,125 cm-1, respectively. These observed data are in congruence with the experimental observations.Conclusion: The identified compounds showed good agreement with the spectrophotometric analysis using DFT methods. In the earlier studies, meropenem’s MIC value was 32 μg mL−1 in OXA-23-positive isolate A2265 compared to the MIC of 1 μg mL−1 in ΔblaOXA-23 A2265. Comparing the CovDock energy and hydrogen-bonding interactions, the predicted results are in good agreement with the experimental data reported earlier. Our results highlight the importance of OXA-23 molecular docking studies and their compliance with the phenotypic results. It will help further in developing newer antibiotics for treating severe infections associated with carbapenem-resistant A. baumannii.

COVID-19 is one of the members of the coronavirus family that can easily assail humans. As of now, 10 million people are infected and above two million people have died from COVID-19 globally. Over the past year, several researchers have made essential advances in discovering potential drugs. Up to now, no efficient drugs are available on the market. The present study aims to identify the potent phytocompounds from different medicinal plants (Zingiber officinale, Cuminum cyminum, Piper nigrum, Curcuma longa, and Allium sativum). In total, 227 phytocompounds were identified and screened against the proteins S-ACE2 and Mpro through structure-based virtual screening approaches. Based on the binding affinity score, 30 active phytocompounds were selected. Amongst, the binding affinity for beta-sitosterol and beta-elemene against S-ACE2 showed −12.0 and −10.9 kcal/mol, respectively. Meanwhile, the binding affinity for beta-sitosterol and beta-chlorogenin against Mpro was found to be −9.7 and −8.4 kcal/mol, respectively. Further, the selected compounds proceeded with molecular dynamics simulation, prime MM-GBSA analysis, and ADME/T property checks to understand the stability, interaction, conformational changes, binding free energy, and pharmaceutical relevant parameters. Moreover, the hotspot residues such as Lys31 and Lys353 for S-ACE2 and catalytic dyad His41 and Cys145 for Mpro were actively involved in the inhibition of viral entry. From the in silico analyses, we anticipate that this work could be valuable to ongoing novel drug discovery with potential treatment for COVID-19.

N(1)-aminopropyl agmatine ureohydrolase (SpeB) is considered an essential enzyme for the growth and survival of thermophiles, it is involved in the biosynthesis of polyamines. The present study investigates the conformational stability and flexibility of Thermus thermophilus HB8 SpeB and its interactions with substrate, N1-aminopropyl agmatine at different physiological conditions to probe the optimal conditions that provide insights on biotechnological applications. As the 3D structure of SpeB is yet to be crystallized, it was modelled and validated using structural bioinformatics methods. To understand the conformational dynamics and also to assess the impact of pH and temperature variables on the tertiary structure of SpeB , atomistic molecular dynamics simulation (MDS) was employed. The MD investigation revealed that 300 K is not optimal for SpeB (apo form) at both acidic pH 4.5, and alkaline pH 8.5, since it exhibited decreased stability and compactness with higher residual flexibility. Further, the stable and strong binding of N1-aminopropyl agmatine with SpeB was observed at following conditions, neutral pH 7 at 353.15 K and alkaline pH 11 at 300 K. Thus, this in silico study provides significant insights into the structural investigations on SpeB along with optimal pH as well as temperature for its ideal enzymatic function. Highlights Structural and dynamic characteristics of T. thermophilus SpeB have been explored in detail Comparative Molecular dynamics simulations were performed to evaluate the effects of both pH and temperature on the structural stability of SpeB SpeB showed pH and temperature-dependent conformational changes that potentially affect substrate binding Structural stability of apo form of SpeB is not optimal at high temperature (363.15 K) in both acidic (pH 5.5) and neutral pH Stable and strong binding affinity of substrate molecule was observed in a neutral pH 7 at 353 K and alkaline pH 11 at 300K [ABSTRACT FROM AUTHOR]