Essential Dynamics Research Articles

Disclosing gate-opening/closing events inside a flexible metal-organic framework loaded with CO2 by reactive and essential dynamics.

We have combined reactive molecular dynamics simulations with principal component analysis to provide a clearer view of the interactions and motion of the CO2 molecules inside a metal-organic framework and the movements of the MOF components that regulate storage, adsorption, and diffusion of the guest species. The tens-of-nanometer size of the simulated model, the capability of the reactive force field tuned to reproduce the inorganic-organic material confidently, and the unconventional use of essential dynamics have effectively disclosed the gate-opening/closing phenomenon, possible coordinations of CO2 at the metal centers, all the diffusion steps inside the MOF channels, the primary motions of the linkers, and the effects of their concerted rearrangements on local CO2 relocations.

Identification of new theobromine-based derivatives as potent VEGFR-2 inhibitors: design, semi-synthesis, biological evaluation, and in silico studies.

This study aimed to design anticancer theobromine derivatives inhibiting VEGFR-2. The new compounds were tested in vitro to evaluate their effectiveness against MCF-7 and HepG2 cancer cell lines. Among these compounds, 15a showed the highest cytotoxicity against HepG2, with an IC50 value of 0.76 μM, and significant anti-proliferative effects on MCF-7, with an IC50 value of 1.08 μM. Notably, the selectivity index of 15a against the two cancer cells was 98.97 and 69.64, respectively. Moreover, 15a demonstrated potent VEGFR-2 inhibitory activity (IC50 = 0.239 μM). Further investigations revealed that 15a induced apoptosis in HepG2 cells, significantly increasing early-stage and late-stage apoptosis percentages from 3.06% and 0.71% to 29.49% and 9.63%, respectively. It also upregulated caspase-3 and caspase-9 levels by 3.45-fold and 2.37-fold, respectively compared to control HepG2 cells. Additionally, 15a inhibited the migration and wound healing ability of HepG2 cells. Molecular docking confirmed the binding affinities of the semi-synthesized compounds to VEGFR-2, consistent with in vitro results. Several computational analyses (DFT, MD simulations, MM-GBSA, PLIP, and essential dynamics) supported the stability of the 15a-VEGFR-2 complex. Overall, the biological and computational findings suggest that compound 15a could be a promising lead compound for the development of a novel apoptotic anticancer agent.

Dubinska muzička pedagogija i četiri načina bivstvovanja

The core dynamics of human development are mirrored in the relationship between verbal and non-verbal experience and communication. This topic is a focus of research not only in developmental psychology, analytical psychology and psychoanalysis, but also in pedagogy and music education. Deep music pedagogy, introduced in this paper, provides a theoretical framework for the exploration of the music nature of the self in educational contexts. The concept of the self is based on the development of four senses of the self, with emphasis on non-verbal and verbal dynamics and the psychoanalytic perspective of the music nature of the self. These essential dynamics are studied in this article as four ways of (music) being and articulated as four educational standards for music education. Deep music pedagogy lays the foundation for music education employing the full developmental and educational potential of the music nature of the self.

Essential Bicycle Dynamics for Microscopic Traffic Simulation: An Example Using the Social Force Model

Essential Bicycle Dynamics for Microscopic Traffic Simulation: An Example Using the Social Force Model

Identification and prioritization of potential therapeutic molecules against LpxA from Acinetobacter baumannii - A computational study.

A. baumannii is a ubiquitously found gram-negative, multi-drug resistant bacterial species from the ESKAPE family of pathogens known to be the causative agent for hospital-acquired infections such as pneumonia, meningitis, endocarditis, septicaemia and urinary tract infections. A.baumannii is implicated as a contributor to bloodstream infections in approximately 2% of all worldwide infections. Hence, exploring novel therapeutic agents against the bacterium is essential. LpxA or UDP-N-acetylglucosamine acetyltransferase is an essential enzyme important in Lipid A biosynthesis which catalyses the reversible transfer of an acetyl group on the glucosamine 3-OH of the UDP-GlcNAc which is a crucial step in the biosynthesis of the protective Lipopolysaccharides (LPS) layer of the bacteria which upon disruption can lead to the elimination of the bacterium which delineates LpxA as an appreciable drug target from A.baumannii. The present study performs high throughput virtual screening of LpxA against the enamine-HTSC-large-molecule library and performs toxicity and ADME screening to identify the three promising lead molecules subjected to molecular dynamics simulations. Global and essential dynamics analysis of LpxA and its complexes along with FEL and MM/PBSA based binding free energy delineate Z367461724 and Z219244584 as potential inhibitors against LpxA from A.baumannii.

Essential collective dynamics analysis reveals nonlocal interactions of alpha-synuclein38-95 monomers with fibrillar seeds

Alpha-synuclein (α-syn) is a cytoplasmic protein commonly found in the nervous system. In solution, α-syn adopts disordered unfolded conformations, although it can also form α-helices upon binding to lipid membranes. Under conditions that are not yet fully understood, α-syn can misfold and aggregate, giving rise to β-sheet rich amyloid fibrils, which then tend to accumulate in degenerating neurons. This leads to Parkinson's disease (PD) and several other conditions collectively termed synucleinopathies. Development of disease-modifying treatments requires detailed understanding of structure and dynamics of α-syn's misfolded aggregates. We have employed 1000ns long, all-atom molecular dynamics simulations to investigate the interaction of monomeric α-syn38-95 fragments, which contain the most important amyloidogenic regions, with preformed fibrillar seeds composed of staggered, β-sheet rich α-syn chains of matching length. The simulations indicate that α-syn38-95 monomers tend to form aggregates with the fibrillar seeds, although we have not observed alignment of the monomeric chains with β-strands of the fibril. To analyze the stability of these aggregates, we have employed the essential collective dynamics method, which allows making accurate assessment of dynamical coupling across individual atoms in macromolecules and supramolecular complexes. The analysis revealed extensive dynamical coupling across initially monomeric α-syn chains and the fibrillar seeds including distal regions thereof that did not contact the monomer directly. We have discussed structural origins of these long-range interactions, their impacts for the stability of α-syn aggregates, and potential implications for the development of anti-PD treatments.

Exploration of Potent Antiviral Phytomedicines from Lauraceae Family Plants against SARS-CoV-2 Main Protease.

A new Coronaviridae strain, Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2), emerged from Wuhan city of China and caused one of the substantial global health calamities in December 2019. Even though several vaccines and drugs have been developed worldwide since COVID-19, a cost-effective drug with the least side effects is still unavailable. Currently, plant-derived compounds are mostly preferred to develop antiviral therapeutics due to its less toxicity, easy access, and cost-effective characteristics. Therefore, in this study, 124 phytochemical compounds from plants of Lauraceae family with medicinal properties were virtually screened against SARS-CoV-2 Mpro. Identification of four phytomolecules, i.e., cassameridine, laetanine, litseferine and cassythicine, with docking scores -9.3, -8.8, -8.6, and -8.6 kcal/mol, respectively, were undertaken by virtual screening, and molecular docking. Furthermore, the molecular dynamic simulation and essential dynamics analysis have contributed in understanding the stability and inhibitory effect of these selected compounds. These phytomolecules can be considered for further in vitro and in vivo experimental study to develop anti-SARS-CoV-2 therapeutics targeting the main protease (Mpro).

Microtubule Severing Enzymes Oligomerization and Allostery: A Tale of Two Domains.

Severing proteins are nanomachines from the AAA+ (ATPases associated with various cellular activities) superfamily whose function is to remodel the largest cellular filaments, microtubules. The standard AAA+ machines adopt hexameric ring structures for functional reasons, while being primarily monomeric in the absence of the nucleotide. Both major severing proteins, katanin and spastin, are believed to follow this trend. However, studies proposed that they populate lower-order oligomers in the presence of cofactors, which are functionally relevant. Our simulations show that the preferred oligomeric assembly is dependent on the binding partners and on the type of severing protein. Essential dynamics analysis predicts that the stability of an oligomer is dependent on the strength of the interface between the helical bundle domain (HBD) of a monomer and the convex face of the nucleotide binding domain (NBD) of a neighboring monomer. Hot spots analysis found that the region consisting of the HBD tip and the C-terminal (CT) helix is the only common element between the allosteric networks responding to nucleotide, substrate, and intermonomer binding. Clustering analysis indicates the existence of multiple pathways for the transition between the secondary structure of the HBD tip in monomers and the structure(s) it adopts in oligomers.

Toward Synthetic Data Generation to Enhance Skidding Detection in Winter Conditions

In this paper, we propose the use of a neural network to identify lateral skidding events of road vehicles used during winter driving conditions. Firstly, data from a simulation model was used to identify the essential vehicle dynamics variables needed and to create the network structure. Then this network was retrained to classify real-world vehicle skidding events. The final network consists of a 3 layer network with 10, 5 and 1 output neurons 13 inputs, 4 outputs and a 5 step time delay. The retrained network was used on a limited set of real vehicle data and confirmed the effectiveness of the network classifying lateral skidding events.

Structural Evaluation and Conformational Dynamics of ZNF141T474I Mutation Provoking Postaxial Polydactyly Type A.

This study delineates the pathogenic association, miss-fold aggregation, and conformational paradigm of a missense variant (c.1420C > T; p.T474I) in ZNF141 gene segregating PAP through a molecular dynamics simulations approach. In ZNF141 protein, helices play a crucial role by attaching three specific target DNA base pairs. In ZNF141T474I protein, H1, H3, and H6 helices attain more flexibility by acquiring loop conformation. The outward disposition of the proximal portion of H9-helix in mutant protein occurs due to the loss of prior beta-hairpins at the C terminal region of the C2-H2 domain. The loss of hydrogen bonds and exposure of hydrophobic residues to solvent and helices turning to loops cause dysfunction of ZNF141 protein. These significant changes in the stability and conformation of the mutant protein were validated using essential dynamics and cross-correlation maps, which revealed that upon point mutation, the overall motion of the proteins and the correlation between them were completely different, resulting in Postaxial polydactyly type A. This study provides molecular insights into the structural association of ZNF141 protein with PAP type A. Identification of active site residues and legends offers new therapeutic targets for ZNF141 protein. Further, it reiterates the functional importance of the last residue of a protein.

Fast Prediction of Flow Field around Airfoils Based on Deep Convolutional Neural Network

We propose a steady-state aerodynamic data-driven method to predict the incompressible flow around airfoils of NACA (National Advisory Committee for Aeronautics) 0012-series. Using the Signed Distance Function (SDF) to parameterize the geometric and flow condition setups, the prediction core of the method is constructed essentially by a consecutive framework of a convolutional neural network (CNN) and a deconvolutional neural network (DCNN). Impact of training parameters on the behavior of the proposed CNN-DCNN model is studied, so that appropriate learning rate, mini-batch size, and random deactivation rate are specified. Tested by “unseen” airfoil geometries and far-field velocities, it is found that the prediction process is three orders of magnitudes faster than a corresponding Computational Fluid Dynamics (CFD) simulation, while relative errors are maintained lower than 1% on most of the sample points. The proposed model manages to capture the essential dynamics of the flow field, as its predictions correspond reasonably with the reconstructed field by proper orthogonal decomposition (POD). The performance and accuracy of the proposed model indicate that the deep learning-based approach has great potential as a robust predictive tool for aerodynamic design and optimization.

Coupling Novel Probes with Molecular Localization Microscopy Reveals Cell Wall Homeostatic Mechanisms in Staphylococcus aureus.

Bacterial cell wall peptidoglycan is essential for viability, and its synthesis is targeted by antibiotics, including penicillin. To determine how peptidoglycan homeostasis controls cell architecture, growth, and division, we have developed novel labeling approaches. These are compatible with super-resolution fluorescence microscopy to examine peptidoglycan synthesis, hydrolysis, and the localization of the enzymes required for its biosynthesis (penicillin binding proteins (PBPs)). Synthesis of a cephalosporin-based fluorescent probe revealed a pattern of PBPs at the septum during division, supporting a model of dispersed peptidoglycan synthesis. Metabolic and hydroxylamine-based probes respectively enabled the synthesis of glycan strands and associated reducing termini of the peptidoglycan to be mapped. Foci and arcs of reducing termini appear as a result of both synthesis of glycan strands and glucosaminidase activity of the major peptidoglycan hydrolase, SagB. Our studies provide molecular level details of how essential peptidoglycan dynamics are controlled during growth and division.

A Comprehensive Review on a Virtual-Synchronous Generator: Topologies, Control Orders and Techniques, Energy Storages, and Applications

In recent years, the penetration of renewable power generations into the electrical grid has substantially increased. Continuous deployment of power electronic-based distributed generations and the reduction of traditional synchronous machines with their essential dynamics in modern power networks are very critical in this change. The use of power electronic inverters leads to the dissociation of sources and loads and lowering the power system inertia. Under power imbalance, this drop causes an elevated rate of change in frequency and frequency divergences, which has a notable impact on the system’s frequency stability. As a result, enhanced control techniques for grid-tied electronic converters are required to secure the power system’s stability and support. The virtual-synchronous generator (VSG) control is used to mimic the dynamics of a rotating synchronous generator and improve the power system’s stability. In this article, the problems of such low-inertia power systems, as well as the VSG technologies, are explored. This research also looks at different control orders and strategies for virtual-synchronous generators (VSG). In addition, the utilization of energy storage and critical matters in VSG and further research recommendations are explained.

Evaluation of rations of high-yielding cows with different energy levels

The materials of the publication reflect the results of scientific research conducted on the Simmental breed dairy cows in the conditions of the “Pchany-Denkovych” farm in the Stryi district of the Lviv region. The study is based on optimizing the normalized energy nutrition of dairy cows with a milk yield of 6000 kg or more per lactation. The main objective of the research was to study the impact of different levels of energy nutrition of cows by lactation phase and its effect on productivity, hematological indicators, the level of individual rumen metabolites, digestibility of essential nutrients, nitrogen balance, and live weight dynamics. Three groups of eight cows each were selected for research. The rations of the experimental animals provided for the inclusion of a protein-fat concentrate in the compound feed at the rate of 5–10 % by nutrition. The main ration consisted of bulk fodder, cereal-bean hay, hay, silage, and balanced compound feed, which were fed from the feed table in the form of a mixture prepared in a feed mixer–the farm practices year-round uniform feeding of cows with a walking yard. The deficiency of mineral substances in the diet was replenished due to iodized salt, monocalcium phosphate, and polysalts of trace elements. Feeding and housing conditions for all experimental animals during the comparison period lasting 15 days were the same and differed in the reference period in terms of nutrient availability in percentages. The analysis of the obtained results showed that increasing the energy supply of cows had a positive effect on milk productivity. In the first period of lactation, the highest yield was obtained from cows of the third group, which indicates that the experimental animals are approaching the maximum possible potential productivity. This trend persists both in the second and third periods. The increased level of energy nutrition due to the use of protein-fat concentrate had a positive effect on the increase in the live weight of cows. During the analysis of the obtained indicators of the rumen content, a probable increase in the number of amylo- and cellulolytic bacteria was revealed - the quantitative advantage (second and third group) compared to the control is 1.52–2.33 and 1.67–2.54 million/ml. A similar pattern is observed in the number of proteolytic bacteria, which contributed to the increase in the enzymatic activity of the microflora. Regarding the digestibility of the primary nutrients of the feed, their growing trend was established in the second and third groups, which confirms the results of the balanced experiment. Thus, animals of the second group are characterized by the highest digestibility and assimilation of nitrogen. Its positive balance was (+7.1) compared to the third and (+3.0) to the first, in which the nitrogen balance was negative. The use of nitrogen for milk in these groups was the highest: from consumed – 31.7 % and from digested – 48.5 %. Thus, the conducted studies provide a reason to recommend that the farm use a protein-fat concentrate of 5% of the diet's total nutrition in the feeding of dairy cows. Its use will ensure an increase in the level of milk productivity and will make it possible to optimize the energy nutrition of cows during the calving period and mid-lactation.

Simulation Assessment of Inlet Parameters and Membrane-Surface-Structure Effects on CO2 Absorption Flux in Membrane Contactors

The management of global carbon dioxide (CO2) emissions is considered one of the main environmental problems facing the modern world. One of the potential techniques for CO2 capture is absorption, using membrane contactor modules. Most of the previous research that dealt with membrane contactor simulations considered the whole membrane surface as the active reaction surface. However, in this paper, a more realistic model of the membrane-contactor module is presented, taking into account the effects of the pore size and surface porosity. CO2 absorption into the monoethanolamine (MEA) solution in hollow fiber membrane-contactor modules was numerically investigated. A computational fluid dynamics simulation was established using essential basic fluid dynamics and mass transfer equations in reactive mode. An algorithmic function was used to present the relations between the CO2 absorption flux and the hollow fiber length, membrane surface pore size, and porosity. The simulation results were compared to previously obtained experimental results without using any fitting parameters, and a good agreement was found with an average error of 8.5%. The validated simulation was then used to predict the effects of the MEA inlet velocity and concentration, the membrane surface pore size, and porosity on the total CO2 absorption flux. A maximum absorption flux of about 1.8 mol/m2·s was achieved at an MEA concentration of 4 M with a pore size of 0.2 microns, a surface porosity of 1%, and an inlet velocity of 0.25 m/s. The extrapolation technique was then used to predict the values of the absorption flux at longer fiber lengths. The concentration profiles around the pores at the gas–liquid contact surface of the membrane were obtained and presented. The proposed model exhibited excellent potential to evaluate the effective reaction surface in hollow fiber membrane contactors. This model could be considered the first step to obtaining accurate predictions of the membrane contactor gas absorption performance based on its surface structure.

Essential Dynamics of the Vertical Wind Shear Affecting the Secondary Eyewall Formation in Tropical Cyclones

Abstract This study investigated the effects of vertical wind shear (VWS) with varying magnitudes on secondary eyewall formation (SEF). It turns out that weak-to-moderate VWS advances the timing of SEF. Strong VWS, however, is unfavorable for SEF in our idealized simulations. VWS affecting SEF mainly lies on its influence on the outer rainbands (ORBs). Under weak-to-moderate VWS, ORBs develop more quickly in the downshear side and have distinct stratiform features in the upshear-left quadrant. The asymmetric inflow associated with the stratiform cooling descends into the boundary layer, reinforcing radial convergence at the radially inward side of ORBs. The radial convergence enhances the low-level convection, resulting in strengthened boundary layer inflow and accelerated low-level tangential wind jet. A budget analysis reveals that tangential advection extends a tangential wind jet farther downwind, forming supergradient winds above the boundary layer in the upshear-right quadrant. As the ORBs propagate into the upshear-right quadrant, the pre-existing supergradient winds enhances the low-level convection, facilitating the closing of the secondary convective ring. The evolution in the upshear side exhibit quadrant-dependent interactions between ORBs and boundary layer. Following that, azimuthal-mean tangential wind acceleration becomes visible, forming the secondary tangential wind maximum. Under strong VWS, the storm is weakened and the boundary layer in the upshear-left quadrant is invaded by low-entropy air, resulting in decreased conditional instability and low-level thermal buoyancy. The decreased stratiform precipitation due to weakened convective activity in the upshear-left quadrant prevents the upshear propagation of ORBs and thus is unfavorable for SEF.

Conformational Heterogeneity and Frustration of the Tumor Suppressor p53 as Tuned by Punctual Mutations.

The conformational heterogeneity of the p53 tumor suppressor, the wild-type (p53wt) and mutated forms, was investigated by a computational approach, including the modeling and all atoms of the molecular dynamics (MD) simulations. Four different punctual mutations (p53R175H, p53R248Q, p53R273H, and p53R282W) which are known to affect the DNA binding and belong to the most frequent hot-spot mutations in human cancers, were taken into consideration. The MD trajectories of the wild-type and mutated p53 forms were analyzed by essential dynamics to extract the relevant collective motions and by the frustration method to evaluate the degeneracy of the energy landscape. We found that p53 is characterized by wide collective motions and its energy landscape exhibits a rather high frustration level, especially in the regions involved in the binding to physiological ligands. Punctual mutations give rise to a modulation of both the collective motions and the frustration of p53, with different effects depending on the mutation. The regions of p53wt and of the mutated forms characterized by a high frustration level are also largely involved in the collective motions. Such a correlation is discussed also in connection with the intrinsic disordered character of p53 and with its central functional role.

A Scoping Review of Three Dimensions for Long-Term COVID-19 Vaccination Models: Hybrid Immunity, Individual Drivers of Vaccinal Choice, and Human Errors.

The virus that causes COVID-19 changes over time, occasionally leading to Variants of Interest (VOIs) and Variants of Concern (VOCs) that can behave differently with respect to detection kits, treatments, or vaccines. For instance, two vaccination doses were 61% effective against the BA.1 predominant variant, but only 24% effective when BA.2 became predominant. While doses still confer protection against severe disease outcomes, the BA.5 variant demonstrates the possibility that individuals who have received a few doses built for previous variants can still be infected with newer variants. As previous vaccines become less effective, new ones will be released to target specific variants and the whole process of vaccinating the population will restart. While previous models have detailed logistical aspects and disease progression, there are three additional key elements to model COVID-19 vaccination coverage in the long term. First, the willingness of the population to participate in regular vaccination campaigns is essential for long-term effective COVID-19 vaccination coverage. Previous research has shown that several categories of variables drive vaccination status: sociodemographic, health-related, psychological, and information-related constructs. However, the inclusion of these categories in future models raises questions about the identification of specific factors (e.g., which sociodemographic aspects?) and their operationalization (e.g., how to initialize agents with a plausible combination of factors?). While previous models separately accounted for natural- and vaccine-induced immunity, the reality is that a significant fraction of individuals will be both vaccinated and infected over the coming years. Modeling the decay in immunity with respect to new VOCs will thus need to account for hybrid immunity. Finally, models rarely assume that individuals make mistakes, even though this over-reliance on perfectly rational individuals can miss essential dynamics. Using the U.S. as a guiding example, our scoping review summarizes these aspects (vaccinal choice, immunity, and errors) through ten recommendations to support the modeling community in developing long-term COVID-19 vaccination models.

Molecular dynamics study of tropical calcific pancreatitis (TCP) associated calcium-sensing receptor single nucleotide variation.

Tropical Calcific Pancreatitis (TCP) is a chronic non-alcoholic pancreatitis characterised by extensive calcification. The disease usually appears at a younger age and is more common in tropical regions. This disease’s progression can lead to pancreatic diabetes, which can subsequently lead to pancreatic cancer. The CASR gene encodes a calcium-sensing receptor (CaSR), which is a GPCR protein of class C. It is expressed in the islets of Langerhans, the parathyroid gland, and other tissues. It primarily detects small gradients in circulating calcium concentrations and couples this information to intracellular signalling, which helps to regulate PTH (parathyroid hormone) secretion and mineral ion homeostasis. From co-leading insulin release, CaSR modulates ductal HCO3− secretion, Ca2+ concentration, cell-cell communication, β-cell proliferation, and intracellular Ca2+ release. In pancreatic cancer, the CaSR limits cell proliferation. TCP-related four novel missense mutations P163R, I427S, D433H and V477A, found in CaSR extracellular domain (ECD) protein, which were reported in the mutTCPdb Database (https://lms.snu.edu.in/mutTCPDB/index.php). P163R mutation occurs in ligand-binding domain 1 (LBD-1) of the CaSR ECD. To investigate the influence of these variations on protein function and structural activity multiple in-silico prediction techniques such as SIFT, PolyPhen, CADD scores, and other methods have been utilized. A 500 ns molecular dynamic simulation was performed on the CaSR ECD crystal structure and the corresponding mutated models. Furthermore, Principal Component Analysis (PCA) and Essential Dynamics analysis were used to forecast collective motions, thermodynamic stabilities, and the critical subspace crucial to CaSR functions. The results of molecular dynamic simulations showed that the mutations P163R, I427S, D433H, and V477A caused conformational changes and decreased the stability of protein structures. This study also demonstrates the significance of TCP associated mutations. As a result of our findings, we hypothesised that the investigated mutations may have an effect on the protein’s structure and ability to interact with other molecules, which may be related to the protein’s functional impairment.

Droperidol as a potential inhibitor of acyl-homoserine lactone synthase from A. baumannii: insights from virtual screening, MD simulations and MM/PBSA calculations.

Acinetobacter baumannii belongs to the ESKAPE family of pathogens and is a multi-drug resistant, gram-negative bacteria which follows the anaerobic form of respiration. A. baumannii is known to be the causative agent of hospital-related infections such as pneumonia, meningitis, endocarditis, septicaemia and a plethora of infections such as urinary tract infections found primarily in immunocompromised patients. These attributes of A. baumannii make it a priority pathogen against which potential therapeutic agents need to be developed. A. baumannii employs the formation of a biofilm to insulate its colonies from the outer environment, which allows it to grow under harsh environmental conditions and develop resistance against various drug molecules. Acyl-homoserine lactone synthase (AHLS) is an enzyme involved in the quorum-sensing pathway in A. baumannii, which is responsible for the synthesis of signal molecules known as acyl-homoserine lactones, which trigger the signalling pathway to regulate the factors involved in biofilm formation and regulation. The present study utilised a homology-modelled structure of AHLS to virtually screen it against the ZINC in trial/FDA-approved drug molecule library to find a subset of potential lead candidates. These molecules were then filtered based on Lipinski's, toxicological and ADME properties, binding affinity, and interaction patterns to delineate lead molecules. Finally, three promising molecules were selected, and their estimated binding affinity values were corroborated using AutoDock 4.2. The identified molecules and a control molecule were subsequently subjected to MD simulations to mimic the physiological conditions of proteinligand-binding interaction under the influence of a GROMOS forcefield. The global and essential dynamics analyses and MM/PBSA based binding free energy computations suggested Droperidol and Cipargamin as potential inhibitors against the binding site of AHLS from A. baumannii. The binding free energy calculations based on the MM/PBSA method showed excellent results for Droperidol (-50.02 ± 4.67kcal/mol) and Cipargamin (-42.29 ± 4.05kcal/mol).