Connection between protein-tyrosine kinase inhibition and coping with oxidative stress in Bacillus subtilis.

In bacteria, attenuation of protein-tyrosine phosphorylation occurs during oxidative stress. The main described mechanism behind this effect is the H2O2-triggered conversion of bacterial phospho-tyrosines to protein-bound 3,4-dihydroxyphenylalanine. This disrupts the bacterial tyrosine phosphorylation-based signaling network, which alters the bacterial polysaccharide biosynthesis. Herein, we report an alternative mechanism, in which oxidative stress leads to a direct inhibition of bacterial protein-tyrosine kinases (BY-kinases). We show that DefA, a minor peptide deformylase, inhibits the activity of BY-kinase PtkA when Bacillus subtilis is exposed to oxidative stress. High levels of PtkA activity are known to destabilize B. subtilis pellicle formation, which leads to higher sensitivity to oxidative stress. Interaction with DefA inhibits both PtkA autophosphorylation and phosphorylation of its substrate Ugd, which is involved in exopolysaccharide formation. Inactivation of defA drastically reduces the capacity of B. subtilis to cope with oxidative stress, but it does not affect the major oxidative stress regulons PerR, OhrR, and Spx, indicating that PtkA inhibition is the main pathway for DefA involvement in this stress response. Structural analysis identified DefA residues Asn95, Tyr150, and Glu152 as essential for interaction with PtkA. Inhibition of PtkA depends also on the presence of a C-terminal α-helix of DefA, which resembles PtkA-interacting motifs from known PtkA activators, TkmA, SalA, and MinD. Loss of either the key interacting residues or the inhibitory helix of DefA abolishes inhibition of PtkA in vitro and impairs postoxidative stress recovery in vivo, confirming the involvement of these structural features in the proposed mechanism.

The emergence of highly resistant and hypervirulent Klebsiella pneumoniae CC14 clone in a tertiary hospital over 8 years.

BACKGROUND: Klebsiella pneumoniae is a major bacterial and opportunistic human pathogen, increasingly recognized as a healthcare burden globally. The convergence of resistance and virulence in K. pneumoniae strains has led to the formation of hypervirulent and multidrug-resistant strains with dual risk, limiting treatment options. K. pneumoniae clones are known to emerge locally and spread globally. Therefore, an understanding of the dynamics and evolution of the emerging strains in hospitals is warranted to prevent future outbreaks. METHODS: In this study, we conducted an in-depth genomic analysis on a large-scale collection of 328 multidrug-resistant (MDR) K. pneumoniae strains recovered from 239 patients from a single major hospital in the western coastal city of Jeddah in Saudi Arabia from 2014 through 2022. We employed a broad range of phylogenetic and phylodynamic methods to understand the evolution of the predominant clones on epidemiological time scales, virulence and resistance determinants, and their dynamics. We also integrated the genomic data with detailed electronic health record (EHR) data for the patients to understand the clinical implications of the resistance and virulence of different strains. RESULTS: We discovered a diverse population underlying the infections, with most strains belonging to Clonal Complex 14 (CC14) exhibiting dominance. Specifically, we observed the emergence and continuous expansion of strains belonging to the dominant ST2096 in the CC14 clade across hospital wards in recent years. These strains acquired resistance mutations against colistin and extended spectrum ß-lactamase (ESBL) and carbapenemase genes, namely blaOXA-48 and blaOXA-232, located on three distinct plasmids, on epidemiological time scales. Strains of ST2096 exhibited a high virulence level with the presence of the siderophore aerobactin (iuc) locus situated on the same mosaic plasmid as the ESBL gene. Integration of ST2096 with EHR data confirmed the significant link between colonization by ST2096 and the diagnosis of sepsis and elevated in-hospital mortality (p-value < 0.05). CONCLUSIONS: Overall, these results demonstrate the clinical significance of ST2096 clones and illustrate the rapid evolution of an emerging hypervirulent and MDR K. pneumoniae in a clinical setting.

Synthesis and Photophysical, Electrochemical, and DFT Studies of Piperidyl and Pyrrolidinyl Chalcones.

Small organic molecules with interesting optical and electrochemical properties find applications as organic luminescent materials. In this work, we report the synthesis of novel chalcones with D-A-D and D-A-D-A architecture, followed by their optical, electrochemical, and computational studies. The absorption band of these compounds occurs at 360-480 nm with emission maxima appearing around 513-552 nm. The large Stokes shifts (Δλ) for all compounds (90-132 nm) suggest intramolecular charge transfer (ICT) in the excited states. The molar absorptivity and fluorescence quantum yields were found to be in the range of 1.7-4.26 × 104 M-1 cm-1 and 0.29-0.39, respectively. The electrochemical parameters were determined by using cyclic voltammetry (CV). Density functional theory (DFT) calculations of all compounds were made by using B3LYP/G (d,p) functionals in chloroform and were found to have a good correlation with experimental results. Preliminary studies of absorption, photoluminescence, CV, and their theoretical correlation suggest that these compounds may be optimized for their applications in optoelectronics, sensing, and bioimaging.

Genome-Wide Mining of Selaginella moellendorffii for Hevein-like Lectins and Their Potential Molecular Mimicry with SARS-CoV-2 Spike Glycoprotein.

Multidisciplinary research efforts on potential COVID-19 vaccine and therapeutic candidates have increased since the pandemic outbreak of SARS-CoV-2 in 2019. This search has become imperative due to the increasing emergences and limited widely available medicines. The presence of bioactive anti-SARS-CoV-2 molecules was examined from various plant sources. Among them is a group of proteins called lectins that can bind carbohydrate moieties. In this article, we present ten novel, chitin-specific Hevein-like lectins that were derived from Selaginella moellendorffii v1.0's genome. The capacity of these lectin homologs to bind with the spike protein of SARS-CoV-2 was examined. Using the HDOCK server, 3D-modeled Hevein-domains were docked to the spike protein's receptor binding domain (RBD). The Smo446851, Smo125663, and Smo99732 interacted with Asn343-located complex N-glycan and RBD residues, respectively, with binding free energies of -17.5, -13.0, and -26.5 Kcal/mol. The molecular dynamics simulation using Desmond and the normal-state analyses via torsional coordinate association for the Smo99732-RBD complex using iMODS is characterized by overall higher stability and minimum deformity than the other lectin complexes. The three lectins interacting with carbohydrates were docked against five individual mutations that frequently occur in major SARS-CoV-2 variants. These were in the spike protein's receptor-binding motif (RBM), while Smo125663 and Smo99732 only interacted with the spike glycoprotein in a protein-protein manner. The precursors for the Hevein-like homologs underwent additional characterization, and their expressional profile in different tissues was studied. These in silico findings offered potential lectin candidates targeting key N-glycan sites crucial to the virus's virulence and infection.

Efficient Authentication Scheme for 5G-Enabled Vehicular Networks Using Fog Computing.

Several researchers have proposed secure authentication techniques for addressing privacy and security concerns in the fifth-generation (5G)-enabled vehicle networks. To verify vehicles, however, these conditional privacy-preserving authentication (CPPA) systems required a roadside unit, an expensive component of vehicular networks. Moreover, these CPPA systems incur exceptionally high communication and processing costs. This study proposes a CPPA method based on fog computing (FC), as a solution for these issues in 5G-enabled vehicle networks. In our proposed FC-CPPA method, a fog server is used to establish a set of public anonymity identities and their corresponding signature keys, which are then preloaded into each authentic vehicle. We guarantee the security of the proposed FC-CPPA method in the context of a random oracle. Our solutions are not only compliant with confidentiality and security standards, but also resistant to a variety of threats. The communication costs of the proposal are only 84 bytes, while the computation costs are 0.0031, 2.0185 to sign and verify messages. Comparing our strategy to similar ones reveals that it saves time and money on communication and computing during the performance evaluation phase.

Molecular evolutionary model based on phylogenetic and mutation analysis of SARS-CoV-2 spike protein sequences from Asian countries: A phylogenomic approach.

The lethal pathogenic severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) infection has caused the COVID-19 pandemic, posing serious risks to people. The clove-like spike (S) protein that distinguishes coronaviruses from other viruses is important for viral pathogenicity, evolution, and transmission. The investigation of the unique structural mutations of the SARS-CoV-2 spike protein among 34 Asian countries, as well as the resulting phylogenetic relationship, provided critical information in understanding the pathogenesis. This can be utilized for the discovery of possible treatments and vaccine development. The current study analyzed and depicted phylogenetic and evolutionary models useful for understanding SARS-CoV-2 human-human transmission dynamics in Asian regions with shared land borders. Further, integrated bioinformatics analysis was performed to predict the pathogenic potential and stability of 53 mutational positions among 34 coronavirus strains. Mutations at positions N969K, D614G and S884F have deleterious effects on protein function. These findings are crucial because the Asian mutations could potentially provide a vaccine candidate with co-protection against all SARS-CoV-2 strains. This region is vulnerable because of the high population density and the volume of domestic and international travel for business and tourism. These discoveries would also aid in the development of plans for governments and the general populace to implement all required biocontainment protocols common to all countries.

AllelePred: A Simple Allele Frequencies Ensemble Predictor for Different Single Nucleotide Variants.

BACKGROUND & OBJECTIVE: Genomic medicine stands to be revolutionized by understanding single nucleotide variants (SNVs) and their expression in single-gene disorders (Mendelian diseases). Computational tools can play a vital role in the exploration of such variations and their pathogenicity. Consequently, we developed the ensemble prediction tool AllelePred to identify deleterious SNVs and disease causative genes. RESULTS: The model utilizes different population genetics backgrounds and restricted criteria for features selection to help generate high accuracy results. In comparison to other tools, such as Eigen, PROVEAN, and fathmm-MKL our classifier achieves higher accuracy (98%), precision (96%), F1 score (93%), and coverage (100%) for different types of coding variants. The new method was also compared against a bioinformatics analytical workflow, which uses gnomAD overall AFs (less than 1%) and CADD (scaled C-score of at least 15). Furthermore, this research highlights the stature of genetic variant sharing and curation. We accumulated a list of highly probable deleterious variants and recommended further experimental validation before medical diagnostic usage. CONCLUSIONS: The ensemble prediction tool AllelePred enables increased accuracy in recognizing deleterious SNVs and the genetic determinants in real clinical data.

IoT-Based Waste Management System in Formal and Informal Public Areas in Mecca.

Urban areas worldwide are in the race to become smarter, and the Kingdom of Saudi Arabia (KSA) is no exception. Many of these have envisaged a chance to establish devoted municipal access networks to assist all kinds of city administration and preserve services needing data connectivity. Organizations unanimously concentrate on sustainability issues with key features of general trends, particularly the combination of the 3Rs (reduce waste, reuse and recycle resources). This paper demonstrates how the incorporation of the Internet of Things (IoT) with data access networks, geographic information systems and combinatorial optimization can contribute to enhancing cities' administration systems. A waste-gathering approach based on supplying smart bins is introduced by using an IoT prototype embedded with sensors, which can read and convey bin volume data over the Internet. However, from another perspective, the population and residents' attitudes directly affect the control of the waste management system. The conventional waste collection system does not cover all areas in the city. It works based on a planned scheme that is implemented by the authorized organization focused on specific popular and formal areas. The conventional system cannot observe a real-time update of the bin status to recognize whether the waste level condition is 'full,' 'not full,' or 'empty.' This paper uses IoT in the container and trucks that secure the overflow and separation of waste. Waste source locations and population density influence the volume of waste generation, especially waste food, as it has the highest amount of waste generation. The open public area and the small space location problems are solved by proposing different truck sizes based on the waste type. Each container is used for one type of waste, such as food, plastic and others, and uses the optimization algorithm to calculate and find the optimal route toward the full waste container. In this work, the situations in KSA are evaluated, and relevant aspects are explored. Issues relating to the sustainability of organic waste management are conceptually analyzed. A genetic-based optimization algorithm for waste collection transportation enhances the performance of waste-gathering truck management. The selected routes based on the volume status and free spaces of the smart bins are the most effective through those obtainable towards the urgent smart bin targets. The proposed system outperforms other systems by reducing the number of locations and smart bins that have to be visited by 46% for all waste types, whereas the conventional and existing systems have to visit all locations every day, resulting in high cost and consumption time.

Integrated Approach to Achieve a Sustainable Organic Waste Management System in Saudi Arabia.

Organic waste management (OWM) has always been a fundamental aspect of human populations. Approaches to OWM must be matched to the characteristics of a certain population. In this consideration, the Kingdom of Saudi Arabia (KSA) is no exception. Organizations are being aligned to focus on sustainability matters sharing significant features with universal trends, especially the integration of 3Rs (reducing waste, reusing, and recycling resources). However, the degree and nature of advancement in the direction of sustainability vary depending on the economic level of a state. High-income economies can afford to pay a higher price to integrate 3Rs technologies. Most recent endeavors have focused on achieving 'Zero Waste', which is costly for low-income developing countries. The expectations of OWM systems in KSA must be estimated. In this work, the situations in KSA and other countries are analyzed, and pertinent aspects are explored. Matters relating to the sustainability of OWM are conceptually assessed. This study proposes an integrated method for an organic waste management system to achieve sustainable OWM in the context of state policy and appropriate frameworks, suitable technology, institutional order, operational and monetary administration, and people consciousness and involvement. A genetic-based waste collection transportation algorithm that enhances the efficiency of waste collection truck management is presented in line with this technology. The selected routes based on the Rfs and IPv are the most efficient among those available for the examined smart bin destinations. The minimum Rfs of selected routes is less than the maximum Rfs of available routes by 2.63%. Also, the minimum IPv of selected routes is less than the maximum IPv of available routes by 27.08%. The proposed integrated approach, including the waste collection transportation algorithm, would be beneficial across a variety of country-specific layouts.

Iridium-Catalyzed C-H Borylation of CF3-Substituted Pyridines.

Iridium-catalyzed C-H borylation of CF3-substituted pyridines is described in this paper. The boronic ester group can be installed on the α, ß, or γ position of pyridine by an appropriate substitution pattern. Sterically governed regioselectivity provides convenient access to a variety of CF3-substituted pyridylboronic esters. These catalytic C-H borylation reactions were carried out neatly without the use of any solvent. Several functional groups, such as halo, ester, alkoxy, amino, etc., are compatible with this methodology. These pyridylboronic esters are amenable to column chromatography and the products were isolated in good to excellent yields. α-Borylated pyridines, although isolated in good yields, do not have a long shelf life. The boronic ester derivatives of these CF3-substituted pyridines can serve as useful precursors in the synthesis regime.

Immuno-Informatics Based Peptides: An Approach for Vaccine Development Against Outer Membrane Proteins of Pseudomonas Genus.

Pseudomonas genus is among the top nosocomial pathogens known to date. Being highly opportunistic, members of pseudomonas genus are most commonly connected with nosocomial infections of urinary tract and ventilator-associated pneumonia. Nevertheless, vaccine development for this pathogenic genus is slow because of no information regarding immunity correlated functional mechanism. In this present work, an immunoinformatics pipeline is used for vaccine development based on epitope-based peptide design, which can result in crucial immune response against outer membrane proteins of pseudomonas genus. A total of 127 outer membrane proteins were analysed, studied and out of them three sequences were obtained to be the producer of non-allergic, highly antigenic T-cell and B-cell epitopes which show good binding affinity towards class II HLA molecules. After performing rigorous screening utilizing docking, simulation, modelling techniques, we had one nonameric peptide (WLLATGIFL)as a good vaccine candidate. The predicted epitopes needs to be further validated for its apt use as vaccine. This work paves a new way with extensive therapeutic application against Pseudomonas genus and their associated diseases.

In silico characterization, docking, and simulations to understand host-pathogen interactions in an effort to enhance crop production in date palms.

Food safety remains a significant challenge despite the growth and development in agricultural research and the advent of modern biotechnological and agricultural tools. Though the agriculturist struggles to aid the growing population's needs, many pathogen-based plant diseases by their direct impact on cell division and tissue development have led to the loss of tons of food crops every year. Though there are many conventional and traditional methods to overcome this issue, the amount and time spend are huge. Scientists have developed systems biology tools to study the root cause of the problem and rectify it. Host-pathogen protein interactions (HPIs) have a promising role in identifying the pathogens' strategy to conquer the host organism. In this paper, the interactions between the host Rhynchophorus ferrugineus (an invasive wood-boring pest that destroys palm) and the pathogens Proteus mirabilis, Serratia marcescens, and Klebsiella pneumoniae are comprehensively studied using protein-protein interactions, molecular docking, and followed by 200 ns molecular dynamic simulations. This study elucidates the structural and functional basis of these proteins leading towards better plant health, production, and reliability.

Structure Dependent Differential Modulation of Aß Fibrillization by Selenadiazole-Based Inhibitors.

Misfolding and fibrillar aggregation of Aß is a characteristic hallmark of Alzheimer's disease and primarily participates in neurodegenerative pathologies. There has been no breakthrough made in the therapeutic regime of Alzheimer's disease while the pharmacological interventions against Aß are designed to sequester and clear Aß burden from the neurological tissues. Based on the physiological relevance of Aß, therapeutic approaches are required to inhibit and stabilize Aß fibrillization, instead of cleaning it from the neurological system. In this context, we have designed a selenadiazole-based library of compounds against the fibrillization paradigm of Aß. Compounds that completely inhibited the Aß fibrillization appeared to stabilize Aß at the monomeric stage as indicated by ThT assay, CD spectrophotometry, and TEM imaging. Partial inhibitors elongated the nucleation phase and allowed limited fibrillization of Aß into smaller fragments with slightly higher ß-sheets contents, while noninhibitors did not interfere in Aß aggregation and resulted in mature fibrils with fibrillization kinetics similar to Aß control. Molecular docking revealed the different binding positions of the compounds for three classes. Complete inhibitors alleviated Aß toxicity to SH-SY5Y neuroblastoma cells and permeated across the blood-brain barrier in zebrafish larvae. The amino acid residues from Aß peptide that interacted with the compounds from all three classes were overlapping and majorly lying in the amyloidogenic regions. However, compounds that stabilize Aß monomers displayed higher association constants (Ka) and lower dissociation constants (Kd) in comparison to partial and noninhibitors, as corroborated by ITC. These results support further structure activity-based preclinical development of these selenadiazole compounds for potential anti-Alzheimer's therapy.

Analysis of natural compounds against the activity of SARS-CoV-2 NSP15 protein towards an effective treatment against COVID-19: a theoretical and computational biology approach.

Coronavirus infectious disease 2019 (COVID-19), a viral infection caused by a novel coronavirus (nCoV), continues to emerge as a serious threat to public health. This pandemic caused by SARS-CoV-2 (severe acute respiratory syndrome-coronavirus-2) has infected globally with 1,550,000 plus deaths to date, representing a high risk to public health. No effective drug or vaccine is available to curb down this deadly virus. The expedition for searching for a potential drug or vaccine against COVID-19 is of massive potential and favour to the community. This study is focused on finding an effective natural compound that can be processed further into a potential inhibitor to check the activity of SARS-CoV-2 with minimal side effects targeting NSP15 protein, which belongs to the EndoU enzyme family. The natural screening suggested two efficient compounds (PubChem ID: 95372568 and 1776037) with dihydroxyphenyl region of the compound, found to be important in the interaction with the viral protein showing promising activity which may act as a potent lead inhibitory molecule against the virus. In combination with virtual screening, modelling, drug likeliness, molecular docking, and 500 ns cumulative molecular dynamics simulations (100 ns for each complex) along with the decomposition analysis to calculate and confirm the stability and fold, we propose 95372568 and 1776037 as novel compounds of natural origin capable of getting developed into potent lead molecules against SARS-CoV-2 target protein NSP15.

QAUST: Protein Function Prediction Using Structure Similarity, Protein Interaction, and Functional Motifs.

The number of available protein sequences in public databases is increasing exponentially. However, a significant percentage of these sequences lack functional annotation, which is essential for the understanding of how biological systems operate. Here, we propose a novel method, Quantitative Annotation of Unknown STructure (QAUST), to infer protein functions, specifically Gene Ontology (GO) terms and Enzyme Commission (EC) numbers. QAUST uses three sources of information: structure information encoded by global and local structure similarity search, biological network information inferred by protein-protein interaction data, and sequence information extracted from functionally discriminative sequence motifs. These three pieces of information are combined by consensus averaging to make the final prediction. Our approach has been tested on 500 protein targets from the Critical Assessment of Functional Annotation (CAFA) benchmark set. The results show that our method provides accurate functional annotation and outperforms other prediction methods based on sequence similarity search or threading. We further demonstrate that a previously unknown function of human tripartite motif-containing 22 (TRIM22) protein predicted by QAUST can be experimentally validated.

In silico virtual screening, characterization, docking and molecular dynamics studies of crucial SARS-CoV-2 proteins.

The ongoing pandemic COVID-19 (COrona Virus Immuno Deficiency-2019) which is caused by SARS-CoV-2 (Severe Acute Respiratory Syndrome-CoronaVirus-2) has emerged as a pandemic with 400,000 plus deaths till date. We do not have any drug or vaccine available for the inhibition of this deadly virus. The expedition for searching a potential drug or vaccine against COVID-19 will be of massive potential and favor. This study is focused on finding an effective natural origin compound which can put a check on the activity of this virus. We chose important proteins from the SARS-CoV-2 genome such as NSP4, NSP15 and RdRp along-with the human ACE2 receptor which is the first point of contact with the virus. Virtual screening and followed up molecular docking resulted in Baicalin and Limonin as the final lead molecules. 200 ns of MD simulation for each protein-ligand complex provides the insights that Baicalin has a potential to target NSP4, NSP15 and RdRp proteins. Limonin which is largely used in traditional Indian medicine system is found to inhibit the human ACE2 receptor (making it inefficient in binding to the receptor binding domain of SARS-CoV-2). Our studies propose Baicalin and Limonin in combination to be studied in vitro and in vivo against COVID-19.Communicated by Ramaswamy H. Sarma.

PATHcre8: A Tool That Facilitates the Searching for Heterologous Biosynthetic Routes.

Developing computational tools that can facilitate the rational design of cell factories producing desired products at increased yields is challenging, as the tool needs to take into account that the preferred host organism usually has compounds that are consumed by competing reactions that reduce the yield of the desired product. On the other hand, the preferred host organisms may not have the native metabolic reactions needed to produce the compound of interest; thus, the computational tool needs to identify the metabolic reactions that will most efficiently produce the desired product. In this regard, we developed the generic tool PATHcre8 to facilitate an optimized search for heterologous biosynthetic pathway routes. PATHcre8 finds and ranks biosynthesis routes in a large number of organisms, including Cyanobacteria. The tool ranks the pathways based on feature scores that reflect reaction thermodynamics, the potentially toxic products in the pathway (compound toxicity), intermediate products in the pathway consumed by competing reactions (product consumption), and host-specific information such as enzyme copy number. A comparison with several other similar tools shows that PATHcre8 is more efficient in ranking functional pathways. To illustrate the effectiveness of PATHcre8, we further provide case studies focused on isoprene production and the biodegradation of cocaine. PATHcre8 is free for academic and nonprofit users and can be accessed at https://www.cbrc.kaust.edu.sa/pathcre8/.

Molecular basis for drug repurposing to study the interface of the S protein in SARS-CoV-2 and human ACE2 through docking, characterization, and molecular dynamics for natural drug candidates.

A novel coronavirus (SARS-CoV-2) identified in Wuhan state of China in 2019 is the causative agent of deadly disease COVID-19. It has spread across the globe (more than 210 countries) within a short period. Coronaviruses pose serious health threats to both humans and animals. A recent publication reported an experimental 3D complex structure of the S protein of SARS-CoV-2 showed that the ectodomain of the SARS-CoV-2 S protein binds to the peptidase domain (PD) of human ACE2 with a dissociation constant (Kd) of ~ 15 nM. In this study, we focused on inhibitors for ACE2: S protein complex using virtual screening and inhibition studies through molecular docking for over 200,000 natural compounds. Toxicity analysis was also performed for the best hits, and the final complex structures for four complexes were subjected to 400 ns molecular dynamics simulations for stability testing. We found two natural origin inhibitors for the S protein: human ACE2 complex (Andrographolide and Pterostilbene) which displayed better inhibition potential for ACE2 receptor and its binding with the S protein of SARS-CoV-2. Comparative studies were also performed to test and verify that these two drug candidates are also better than hydroxychloroquine which is known to inhibit this complex. However, we needed better potential drug candidates to overcome the side effects of hydroxychloroquine. Supplementary experimental studies need to be carried forward to corroborate the viability of these two new inhibitors for ACE2: S protein complex so as to curb down COVID-19.

A Comprehensive Review of Aminochalcones.

Chalcones, members of the flavonoid family, display a plethora of interesting biological activities including but not limited to antioxidant, anticancer, antimicrobial, anti-inflammatory, and antiprotozoal activities. The literature cites the synthesis and activity of a range of natural, semisynthetic, and synthetic chalcones. The current review comprehensively covers the literature on amino-substituted chalcones and includes chalcones with amino-groups at various positions on the aromatic rings as well as those with amino-groups containing mono alkylation, dialkylation, alkenylation, acylation, and sulfonylation. The aminochalcones are categorized according to their structure, and the corresponding biological activities are discussed as well. Some compounds showed high potency against cancer cells, microbes, and malaria, whereas others did not. The purpose of this review is to serve as a one-stop location for information on the aminochalcones reported in the literature in recent years.

Molecular basis of the beta-lactamase protein using comparative modelling, drug screening and molecular dynamics studies to understand the resistance of ß-lactam antibiotics.

Beta-lactamase (ampC) in general causes the onset of antibiotic resistance in pathogenic bacteria against the ß-lactam antibiotics. Morganella morganii which belongs to the Proteae tribe of the Enterobacteriaceae family is a Gram-negative bacillus. Gram-negative bacteria are the key problematic agents among the human population in overexpressing resistance against ß-lactam antibiotics. These ß-lactam antibiotics being experimentally well studied still lack the key information and mechanism for their resistance. The structural information of the ampC protein is unknown and poorly studied; hence, it is the need of the hour to find effective inhibitors against it. In our study, the prediction of the three-dimensional structure of ampC protein from Morganella morganii was performed using a comparative modelling approach. The predicted structure was energetically stabilized and functional conformations were mapped through 100-ns molecular dynamics simulation runs. Also, Ramachandran plot shows the model to be stereo-chemically stable with most residues found under core allowed regions. Drug screening with several experimentally tested inhibitors was then confirmed to check the activity against ampC protein using an AutoDock tool. The results suggested OncoglabrinolC molecule as the best inhibitor (out of 21 drug molecules) with a binding affinity of - 11.44 kcal/mol. Anti-bacterial/anti-parasitic inhibitors have not only been used against bacterial infections, but later reports have also shown them to work against deadly viruses such as SARS-CoV2. This key structural and inhibitory information is certain to help in the discovery of specific and potent substitute therapeutic drugs and the development of experimental procedures against human infection.