Binding Free Energy Calculations Research Articles

In silico analysis and characterization of potential inhibitors of MmaA3, a methoxy mycolic acid synthase from Mycobacterium tuberculosis

The emergence of the multi-and extensively drug-resistant (MDR and XDR) strains of Mycobacterium tuberculosis (M.tb), necessitates paradigm-shifting therapeutic approaches. The impermeable waxy lipid layer, primarily composed of mycolic acids, is a key factor in conferring resistance to conventional drugs. This study introduces a novel strategy to combat drug resistance by targeting Methoxy mycolic acid synthase 3 (MmaA3), a critical enzyme in the mycolic acid biosynthesis pathway. MmaA3 is responsible for the O-methylation of hydroxymycolate precursors and emerges as a promising therapeutic target. Through homology-based modeling, we generated a three-dimensional structure of MmaA3, providing crucial insights into its structural characteristics. High throughput virtual screening was performed against the MmaA3 model, using diverse sources: knowledge-based, FDA-approved Drugbank, and Asinex-Elite libraries. Through rigorous computational analyses, including binding affinity assessments, molecular interactions analysis, and binding free energy calculations, potential inhibitors of MmaA3 have been identified. Subsequent validation studies evaluated the stability of top protein-ligand complexes, and free energy calculations using molecular dynamics simulations. The stability of complexes within the catalytic site was confirmed through RMSD and RMSF profile analyses. Furthermore, binding free energy calculations using the MM-GBSA approach revealed significant binding affinity of identified ligands for MmaA3 target protein, comparable to its substrate/cofactors. These findings underscore the potential of the proposed molecules as candidates for further experimental exploration, offering promising avenues for the development of effective inhibitors against M.tb. Overall, our research contributes to significantly advancing the formulation of progressive therapeutic strategies in combating drug-resistant tuberculosis. Communicated by Ramaswamy H. Sarma

In silico evaluation of anti-colorectal cancer inhibitors by Resveratrol derivatives targeting Armadillo repeats domain of APC: molecular docking and molecular dynamics simulation.

Colorectal cancer is the second leading cause of cancer-related deaths. In 2018, there were an estimated 1.8 million cases, and this number is expected to increase to 2.2 million by 2030. Despite its prevalence, the current therapeutic option has a lot of side effects and limitations. Therefore, this study was designed to employ a computational approach for the identification of anti-cancer inhibitors against colorectal cancer using Resveratrol derivatives. Initially, the pass prediction spectrum of 50 derivatives was conducted and selected top seven compounds based on the maximum pass prediction score. After that, a comprehensive analysis, including Lipinski Rule, pharmacokinetics, ADMET profile study, molecular orbitals analysis, molecular docking, molecular dynamic simulations, and MM-PBSA binding free energy calculations. The reported binding affinity ranges of Resveratrol derivatives from molecular docking were -6.1 kcal/mol to -7.9 kcal/mol against the targeted receptor of human armadillo repeats domain of adenomatous polyposis coli (APC) (PDB ID: 3NMW). Specifically, our findings reported that two compounds [(03) Resveratrol 3-beta-mono-D-glucoside, and (29) Resveratrol 3-Glucoside] displayed the highest level of effectiveness compared to all other derivatives (-7.7 kcal/mol and -7.9 kcal/mol), and favorable drug-likeness, and exceptional safety profiles. Importantly, almost all the molecules were reported as free from toxic effects. Subsequently, molecular dynamic simulations conducted over 100ns confirmed the stability of the top two ligand-protein complexes. These findings suggest that Resveratrol derivatives may be effective drug candidate to manage the colorectal cancer. However, further experimental research, such as in vitro/in vivo studies, is essential to validate these computational findings and confirm their practical value.

A structure-based pharmacophore modelling approach to identify and design new neprilysin (NEP) inhibitors: An in silico-based investigation

Neutral endopeptidase or neprilysin (NEP) cleaves the natriuretic peptides, bradykinin, endothelin, angiotensin II, amyloid β protein, substance P, etc., thus modulating their effects on heart, kidney, and other organs. NEP has a proven role in hypertension, heart disease, renal disease, Alzheimer's, diabetes, and some cancers. NEP inhibitor development has been in focus since the US FDA approved a combination therapy of angiotensin II type 1 receptor inhibitor (valsartan) and NEP inhibitor (sacubitril) for use in heart failure. Considering the importance of NEP inhibitors the present work focuses on the designing of a potential lead for NEP inhibition. A structure-based pharmacophore modelling approach was employed to identify NEP inhibitors from the pool of 1140 chemical entities obtained from the ZINC database. Based on the docking score and pivotal interactions, ten molecules were selected and subjected to binding free energy calculations and ADMET predictions. The top two compounds were studied further by molecular dynamics simulations to determine the stability of the ligand-receptor complex. ZINC0000004684268, a phenylalanine derivative, showed affinity and complex stability comparable to sacubitril. However, in silico studies indicated that it may have poor pharmacokinetic parameters. Therefore, the molecule was optimized using bioisosteric replacements, keeping the phenylalanine moiety intact, to obtain five potential lead molecules with an acceptable pharmacokinetic profile. The works thus open up the scope to further corroborate the present in silico findings with the biological analysis.

QM, molecular docking and molecular dynamics investigation on acidic phospholipase A2 2 protein and acidic phospholipase A2 3 protein with silane dimethyl

Phytochemicals and non-nutritive plant substances can protect humans from various diseases by possessing anti-inflammatory or anti-disease properties. The Andrographis Paniculata species has been the primary focus of extensive pharmacological and phytochemical research. QM concepts are being applied scientifically in chemical and biological problems, with molecular docking and molecular dynamics techniques being crucial in-silico drug development. Absorptions in Andrographis Paniculata come from charge transfer due to visible light's energy emissions, with GCMS– results indicating its chemical components possess antibacterial properties. The PES concept aids in the intuitive understanding of mathematical concepts, while RDG recreates the complete distribution of electronic pairings, including interatomic bonding regions, lone pairs, and cores. Molecular dynamics is crucial for protein-ligand docking due to its accurate binding free energy calculations and profound understanding of the dynamic nature of protein-ligand interactions.

Structural insights into the potential binding sites of Cathepsin D using molecular modelling techniques

Alzheimer’s disease (AD) is the most prevalent type of dementia caused by the accumulation of amyloid beta (Aβ) peptides. The extracellular deposition of Aβ peptides in human AD brain causes neuronal death. Therefore, it has been found that Aβ peptide degradation is a possible therapeutic target for AD. CathD has been known to breakdown amyloid beta peptides. However, the structural role of CathD is not yet clear. Hence, for the purpose of gaining a deeper comprehension of the structure of CathD, the present computational investigation was performed using virtual screening technique to predict CathD's active site residues and substrate binding mode. Ligand-based virtual screening was implemented on small molecules from ZINC database against crystal structure of CathD. Further, molecular docking was utilised to investigate the binding mechanism of CathD with substrates and virtually screened inhibitors. Localised compounds obtained through screening performed by PyRx and AutoDock 4.2 with CathD receptor and the compounds having highest binding affinities were picked as; ZINC00601317, ZINC04214975 and ZINCC12500925 as our top choices. The hydrophobic residues Viz. Gly35, Val31, Thr34, Gly128, Ile124 and Ala13 help stabilising the CathD-ligand complexes, which in turn emphasises substrate and inhibitor selectivity. Further, MM-GBSA approach has been used to calculate binding free energy between CathD and selected compounds. Therefore, it would be beneficial to understand the active site pocket of CathD with the assistance of these discoveries. Thus, the present study would be helpful to identify active site pocket of CathD, which could be beneficial to develop novel therapeutic strategies for the AD.

Binding Mechanism of Inhibitors to BRD4 and BRD9 Decoded by Multiple Independent Molecular Dynamics Simulations and Deep Learning.

Bromodomain 4 and 9 (BRD4 and BRD9) have been regarded as important targets of drug designs in regard to the treatment of multiple diseases. In our current study, molecular dynamics (MD) simulations, deep learning (DL) and binding free energy calculations are integrated to probe the binding modes of three inhibitors (H1B, JQ1 and TVU) to BRD4 and BRD9. The MD trajectory-based DL successfully identify significant functional function domains, such as BC-loop and ZA-loop. The information from the post-processing analysis of MD simulations indicates that inhibitor binding highly influences the structural flexibility and dynamic behavior of BRD4 and BRD9. The results of the MM-GBSA calculations not only suggest that the binding ability of H1B, JQ1 and TVU to BRD9 are stronger than to BRD4, but they also verify that van der Walls interactions are the primary forces responsible for inhibitor binding. The hot spots of BRD4 and BRD9 revealed by residue-based free energy estimation provide target sites of drug design in regard to BRD4 and BRD9. This work is anticipated to provide useful theoretical aids for the development of selective inhibitors over BRD family members.

On Analytical Corrections for Restraints in Absolute Binding Free Energy Calculations.

Double decoupling absolute binding free energy simulations require an intermediate state at which the ligand is held solely by restraints in a position and orientation resembling the bound state. One possible choice consists of one distance, two angle, and three dihedral angle restraints. Here, I demonstrate that in practically all cases the analytical correction derived under the rigid rotator harmonic oscillator approximation is sufficient to account for the free energy of the restraints.

Effect of quercetin on the protein-substrate interactions in SIRT6: Insight from MD simulations

SIRT6 is of interest for its promising effect in the treatment of aging-related diseases. Studies have shown quercetin (QUE) and its derivatives have varying degrees of effect on the catalytic effect of SIRT6. In the research, the effect of QUE on the protein-substrate interaction in the SIRT6-mediated mono-ADP ribosylation system was investigated by conventional molecular dynamics (MD) simulations combined with MM/PBSA binding free energy calculations. The results show that QUE can bind stably to SIRT6 with the binding energy of −22.8 kcal/mol and further affect the atomic interaction between SIRT6 and NAD+ (or H3K9), resulting in an increased affinity between SIRT6-NAD+ and decreased SIRT6-H3K9 binding capacity. At the same time, the binding of QUE can also alter some structural characteristics of the protein, with large shifts occurring in the residue regions involving the N-terminal (residues 1–27), Rossmann fold regions (residues 55–92), and ZBD (residues 164–179). Thus, QUE shows great potential as a scaffold for the design of novel potent SIRT6 modulators.

Investigating the role of functional mutations in leucine binding to Sestrin2 in aging and age-associated degenerative pathologies using structural and molecular simulation approaches

Leucine is the native known ligand of Sestrin2 (Sesn2) and its interaction with Sesn2 is particularly important, as it influences the activity of mTOR in aging and its associated pathologies. It is important to find out how leucine interacts with Sesn2 and how mutations in the binding pocket of leucine affect the binding of leucine. Therefore, this study was committed to investigating the impact of non-synonymous mutations by incorporating a broad spectrum of simulation techniques, from molecular dynamics to free energy calculations. Our study was designed to model the atomic-scale interactions between leucine and mutant forms of Sesn2. Our results demonstrated that the interaction paradigm for the mutants has been altered thus showing a significant decline in the hydrogen bonding network. Moreover, these mutations compromised the dynamic stability by altering the conformational flexibility, sampling time, and leucine-induced structural constraints that consequently caused variation in the binding and structural stability. Molecular dynamics-based flexibility analysis revealed that the regions 217–339 and 371–380 demonstrated a higher fluctuation. Noteworthy, these regions correspond to a linker (217–339) and a loop (371–380) that cover the leucine binding cavity that is critical for the ‘latch’ mechanism in the N-terminal, which is essential for leucine binding. Further validation of reduced binding and modified internal motions caused by the mutants was obtained through binding free energy calculations, principal components analysis (PCA), and free energy landscape (FEL) analysis. By unraveling the molecular intricacies of Sesn2-leucine interactions and their mutations, we hope to pave the way for innovative strategies to combat the inevitable tide of aging and its associated diseases. Communicated by Ramaswamy H. Sarma

Long-timescale atomistic simulations uncover loss-of-function mechanisms of uncharacterized Angiogenin mutants associated with ALS

Amyotrophic Lateral Sclerosis (ALS) is a devastating neurodegenerative disease characterized by progressive degeneration of motor neurons, resulting in respiratory failure and mortality within 3–5 years. Mutations in the Angiogenin (ANG) cause loss of ribonucleolytic and nuclear translocation activities, contributing to ALS pathogenesis. This study focused on investigating two uncharacterized ANG mutations, T11S and R122H, newly identified in the Project Mine consortium. Using extensive computational analysis, including structural modeling and microsecond-timescale molecular dynamics (MD) simulations, we observed conformational changes in the catalytic residue His114 of ANG induced by T11S and R122H mutations. These alterations impaired ribonucleolytic activity, as inferred through molecular docking and binding free energy calculations. Gibbs free energy landscape and residue-residue interaction network analysis further supported our findings, revealing the energetic states and allosteric pathway from the mutated site to His114. Additionally, we assessed the binding of NCI-65828, an inhibitor of ribonucleolytic activity of ANG, and found reduced effectiveness in binding to T11S and R122H mutants when His114 assumed a non-native conformation. This highlights the crucial role of His114 and its association with ALS. Elucidating the relationship between physical structure and functional dynamics of frequently mutated ANG mutants is essential for understanding ALS pathogenesis and developing more effective therapeutic interventions.

In-silico screening and identification of glycomimetic as potential human sodium-glucose co-transporter 2 inhibitor

Sodium-glucose co-transporter 2 (SGLT2) is one of the important targets against type II diabetes mellitus. A typical SGLT2 inhibitor acts by inhibiting glucose reabsorption, thus lowering the blood glucose level. Unlike SGLT1, SGLT2 is responsible for almost 90% glucose reabsorption from glomerular filtrate. The current SGLT2 inhibitors include gliflozins, often prescribed as second or third-line agents in diabetes mellitus. The SGLT2 inhibitors also benefit patients with heart and kidney disease. Due to instability issues with the natural O-aryl glycoside analogues C-glycoside analogues were developed and showed improved stability. Despite enhanced bioavailability and selectivity of newer derivatives, some serious side effects are associated with gliflozin analogues. At the present study, we applied in-silico approaches to find new glycomimetic compounds as potent SGLT2 inhibitors that could show improvement in side effects associated with current analogues. This work applied both ligand-based and structure-based drug approaches to find potential compounds. We developed a 3D-QSAR method to screen potential inhibitors from a library of ten thousand compounds and performed docking studies. The compounds were ranked based on predicted pIC50 and docking score. An initial screening of five thousand compounds was conducted, and the subsequently selected top 12 compounds were based on binding free energy calculations. These selected compounds were subjected to molecular dynamics (MD) simulations. Remarkably, our simulations identified nine compounds that exhibited significant and sustained binding affinity compared to the co-crystallized Empagliflozin. Collectively, considering the anticipated pharmacokinetic profiles and toxicity assessments, several of these compounds emerged as promising candidates for further in-depth evaluation.

An Ensemble Docking Approach for Analyzing and Designing Aptamer Heterodimers Targeting VEGF165.

Vascular endothelial growth factor 165 (VEGF165) is a prominent isoform of the VEGF-A protein that plays a crucial role in various angiogenesis-related diseases. It is homodimeric, and each of its monomers is composed of two domains connected by a flexible linker. DNA aptamers, which have emerged as potent therapeutic molecules for many proteins with high specificity and affinity, can also work for VEGF165. A DNA aptamer heterodimer composed of monomers of V7t1 and del5-1 connected by a flexible linker (V7t1:del5-1) exhibits a greater binding affinity with VEGF165 compared to either of the two monomers alone. Although the structure of the complex formed between the aptamer heterodimer and VEGF165 is unknown due to the highly flexible linkers, gaining structural information will still be valuable for future developments. Toward this end of accessing structural information, we adopt an ensemble docking approach here. We first obtain an ensemble of structures for both VEGF165 and the aptamer heterodimer by considering both small- and large-scale motions. We then proceed through an extraction process based on ensemble docking, molecular dynamics simulations, and binding free energy calculations to predict the structures of the VEGF165/V7t1:del5-1 complex. Through the same procedures, we reach a new aptamer heterodimer that bears a locked nucleic acid-modified counterpart of V7t1, namely RNV66:del5-1, which also binds well with VEGF165. We apply the same protocol to the monomeric units V7t1, RNV66, and del5-1 to target VEGF165. We observe that V7t1:del5-1 and RNV66:del5-1 show higher binding affinities with VEGF165 than any of the monomers, consistent with experiments that support the notion that aptamer heterodimers are more effective anti-VEGF165 aptamers than monomeric aptamers. Among the five different aptamers studied here, the newly designed RNV66:del5-1 shows the highest binding affinity with VEGF165. We expect that our ensemble docking approach can help in de novo designs of homo/heterodimeric anti-angiogenic drugs to target the homodimeric VEGF165.

De novo design of drug-binding proteins with predictable binding energy and specificity.

The de novo design of small molecule-binding proteins has seen exciting recent progress; however, high-affinity binding and tunable specificity typically require laborious screening and optimization after computational design. We developed a computational procedure to design a protein that recognizes a common pharmacophore in a series of poly(ADP-ribose) polymerase-1 inhibitors. One of three designed proteins bound different inhibitors with affinities ranging from <5 nM to low micromolar. X-ray crystal structures confirmed the accuracy of the designed protein-drug interactions. Molecular dynamics simulations informed the role of water in binding. Binding free energy calculations performed directly on the designed models were in excellent agreement with the experimentally measured affinities. We conclude that de novo design of high-affinity small molecule-binding proteins with tuned interaction energies is feasible entirely from computation.

Computational Insights into the Interaction of the Conserved Cysteine-Noose Domain of the Human Respiratory Syncytial Virus G Protein with the Canonical Fractalkine Binding site of Transmembrane Receptor CX3CR1 Isoforms.

The human Respiratory Syncytial Virus (hRSV) stands as one of the most common causes of acute respiratory diseases. The infectivity of this virus is intricately linked to its membrane proteins, notably the attachment glycoprotein (G protein). The latter plays a key role in facilitating the attachment of hRSV to respiratory tract epithelial cells, thereby initiating the infection process. The present study aimed to characterize the interaction of the conserved cysteine-noose domain of hRSV G protein (cndG) with the transmembrane CX3C motif chemokine receptor 1 (CX3CR1) isoforms using computational tools of molecular modeling, docking, molecular dynamics simulations, and binding free energy calculations. From MD simulations of the molecular system embedded in the POPC lipid bilayer, we showed a stable interaction of cndG with the canonical fractalkine binding site in the N-terminal cavity of the CX3CR1 isoforms and identified that residues in the extracellular loop 2 (ECL2) region and Glu279 of this receptor are pivotal for the stabilization of CX3CR1/cndG binding, corroborating what was reported for the interaction of the chemokine fractalkine with CX3CR1 and its structure homolog US28. Therefore, the results presented here contribute by revealing key structural points for the CX3CR1/G interaction, allowing us to better understand the biology of hRSV from its attachment process and to develop new strategies to combat it.

Understanding the Reversible Binding of a Multichain Protein-Protein Complex through Free-Energy Calculations.

We demonstrate that the binding affinity of a multichain protein-protein complex, insulin dimer, can be accurately predicted using a streamlined route of standard binding free-energy calculations. We find that chains A and C, which do not interact directly during binding, stabilize the insulin monomer structures and reduce the binding affinity of the two monomers, therefore enabling their reversible association. Notably, we confirm that although classical methods can estimate the binding affinity of the insulin dimer, conventional molecular dynamics, enhanced sampling algorithms, and classical geometrical routes of binding free-energy calculations may not fully capture certain aspects of the role played by the noninteracting chains in the binding dynamics. Therefore, this study not only elucidates the role of noninteracting chains in the reversible binding of the insulin dimer but also offers a methodological guide for investigating the reversible binding of multichain protein-protein complexes utilizing streamlined free-energy calculations.

Integrated track of nano-informatics coupling with the enrichment concept in developing a novel nanoparticle targeting ERK protein in Naegleria fowleri

Abstract Naegleria fowleri is a free-living amoeba that causes primary amoebic meningoencephalitis. Despite combination drug therapies, N. fowleri is not sensitive to current drug therapies, contributing to the pathogen’s mortality rate of 98%. To enable rational drug designing, this study has proposed an integrated track of nanotechnology coupling with the enrichment concept. In the current study, zinc oxide nanoparticles (ZNP) were screened against ERK protein, which is responsible for the production of pro-inflammatory cytokines that cause brain disturbance in N. fowleri infection. Furthermore, an enrichment analysis has been executed to increase the efficiency of the ZNP through the addition of two amines and one chlorine group. The computational prediction of zeta potential, cytotoxicity, organ toxicity, calculations of binding free energy, and ADMET analysis shows that it is stable and possesses no toxic effect. Amine + chlorine enriched ZNP resulted in a binding energy of −7.8 kcal/mol, a zeta potential reliability of −40 mV, a cytotoxicity of −0.0002, inactive against all the targeted organ models, ADMET profiling shows a molecular weight of 320.54 g/mol, a lipophilicity of −0.99, high water solubility, and good gastrointestinal tract absorption. This proposed invention represents the future work for in vitro in combating this devastating disease toward a reliable therapeutic target with drugs that specifically aimed to inhibit the infection.

Structure-based virtual screening of novel USP5 inhibitors targeting the zinc finger ubiquitin-binding domain

The equilibrium of cellular protein levels is pivotal for maintaining normal physiological functions. USP5 belongs to the deubiquitination enzyme (DUBs) family, controlling protein degradation and preserving cellular protein homeostasis. Aberrant expression of USP5 is implicated in a variety of diseases, including cancer, neurodegenerative diseases, and inflammatory diseases. In this paper, a multi-level virtual screening (VS) approach was employed to target the zinc finger ubiquitin-binding domain (ZnF-UBD) of USP5, leading to the identification of a highly promising candidate compound 0456–0049. Molecular dynamics (MD) simulations were then employed to assess the stability of complex binding and predict hotspot residues in interactions. The results indicated that the candidate stably binds to the ZnF-UBD of USP5 through crucial interactions with residues ARG221, TRP209, GLY220, ASN207, TYR261, TYR259, and MET266. Binding free energy calculations, along with umbrella sampling (US) simulations, underscored a superior binding affinity of the candidate relative to known inhibitors. Moreover, US simulations revealed conformational changes of USP5 during ligand dissociation. These insights provide a valuable foundation for the development of novel inhibitors targeting USP5.

Nonbonded Force Field Parameters from MBIS Partitioning of the Molecular Electron Density Improve Binding Affinity Predictions of the T4-Lysozyme Double Mutant.

The use of computer simulation for binding affinity prediction is growing in drug discovery. However, its wider use is constrained by the accuracy of the free energy calculations. The key sources of error are the force fields used to depict molecular interactions and insufficient sampling of the configurational space. To improve the quality of the force field, we developed a Python-based computational workflow. The workflow described here uses the minimal basis iterative stockholder (MBIS) method to determine atomic charges and Lennard-Jones parameters from the polarized molecular density. This is done by performing electronic structure calculations on various configurations of the ligand when it is both bound and unbound. In addition, we validated a simulation procedure that accounts for the protein and ligand degrees of freedom to precisely calculate binding free energies. This was achieved by comparing the self-adjusted mixture sampling and nonequilibrium thermodynamic integration methods using various protein and ligand conformations. The accuracy of predicting binding affinity is improved by using MBIS-derived force field parameters and a validated simulation procedure. This improvement surpasses the chemical precision for the eight aromatic ligands, reaching a root-mean-square error of 0.7 kcal/mol.

Role of UDP-N-acetylmuramic acid in the regulation of MurA activity revealed by molecular dynamics simulations.

The peptidoglycan biosynthesis pathway plays a vital role in bacterial cells, and facilitates peptidoglycan layer formation, a fundamental structural component of the bacterial cell wall. The enzymes in this pathway are candidates for antibiotic development, as most do not have mammalian homologues. The UDP-N-acetylglucosamine (UNAG) enolpyruvyl transferase enzyme (MurA) in the peptidoglycan pathway cytoplasmic step is responsible for the phosphoenolpyruvate (PEP)-UNAG catalytic reaction, forming UNAG enolpyruvate and inorganic phosphate. Reportedly, UDP-N-acetylmuramic acid (UNAM) binds tightly to MurA forming a dormant UNAM-PEP-MurA complex and acting as a MurA feedback inhibitor. MurA inhibitors are complex, owing to competitive binding interactions with PEP, UNAM, and UNAG at the MurA active site. We used computational methods to explore UNAM and UNAG binding. UNAM showed stronger hydrogen-bond interactions with the Arg120 and Arg91 residues, which help to stabilize the closed conformation of MurA, than UNAG. Binding free energy calculations using end-point computational methods showed that UNAM has a higher binding affinity than UNAG, when PEP is attached to Cys115. The unbinding process, simulated using τ-random acceleration molecular dynamics, showed that UNAM has a longer relative residence time than UNAG, which is related to several complex dissociation pathways, each with multiple intermediate metastable states. This prevents the loop from opening and exposing the Arg120 residue to accommodate UNAG and potential new ligands. Moreover, we demonstrate the importance of Cys115-linked PEP in closed-state loop stabilization. We provide a basis for evaluating novel UNAM analogues as potential MurA inhibitors. PUBLIC SIGNIFICANCE: MurA is a critical enzyme involved in bacterial cell wall biosynthesis and is involved in antibiotic resistance development. UNAM can remain in the target protein's active site for an extended time compared to its natural substrate, UNAG. The prolonged interaction of this highly stable complex known as the 'dormant complex' comprises UNAM-PEP-MurA and offers insights into antibiotic development, providing potential options against drug-resistant bacteria and advancing our understanding of microbial biology.

Abstract 5978: Therapeutic targeting of MELK using a drug repurposing approach to combat TNBC cells

Abstract Background: Triple-negative breast cancer (TNBC) is the most aggressive subtype of breast cancer linked to high chemo-resistant metastatic cases and limited therapeutic options due to the absence of conventional bioreceptors. Therefore, to treat TNBC, it is imperative to identify promising druggable biological targets. Experimental Procedures: An integrated bioinformatic analysis of microarray datasets was performed to identify significantly differentially expressed genes (DEGs) in TNBC. For selecting a potent therapeutic target, the function and significance of the upregulated DEGs in TNBC was investigated by an in silico study employing the UALCAN portal, String database, KM plotter, and Enrichr tools. This analysis included gene expression validation, insights into protein-protein interactions, survival analysis, and pathway mapping of the genes. To obtain potent drugs binding to the selected target MELK (maternal embryonic leucine zipper kinase), a drug repurposing approach was employed starting with virtual screening followed by molecular dynamic simulation (MDS) using GROMACS. Further, the anti-cancer activity of the top two drugs was validated by live-dead imaging, gene expression analyses, MTT-based cell viability and ROS detection assays. Results: Based on a stringent criterion for significant DEG identification (log2|FC|&amp;gt;1 &amp; adjust P-value &amp;lt; 0.05), 25 overlapping upregulated genes were obtained from three selected datasets. Further, in silico analysis revealed that MELK is significantly upregulated across the four stages and subtypes of breast cancer, including TNBC. Higher MELK expression and its oncogenic interactions correlated with poor overall survival of TNBC patients. Evidence suggests that the existing inhibitor for MELK (OTSSP167) has shown poor specificity. Therefore, to block its activity, a library of 1293 FDA-approved drugs was screened against the kinase domain of MELK. MDS study and analysis using parameters like RMSD, RMSF and pair distance revealed that the top 10 drugs were strongly stabilized by H-bonds in the binding pocket of MELK, with minimal deviation and reduced fluctuations of MELK upon drug binding. Binding free energy calculation of drug-MELK interaction using the MM-PBSA method revealed that nine drugs possessed higher binding energy than the inhibitor. The top two drugs obtained from the study (originally kinase and reductase inhibitors respectively) were further validated for their in vitro anti-cancer efficacy in MDA-MB-231 and MDA-MB-468 cells. Treatment with these drugs exhibited (a) a dose-dependent decrease in proliferation, (b) significant cell death, (c) a marked increase in the cellular ROS levels, and (d) a decrease in the expression of MELK and its downstream targets in TNBC cell lines. Conclusion: The present study opens the avenue for using repurposed drugs as potential therapeutic molecules against MELK activity to combat TNBC progression. Citation Format: Arisha Arora, Shilpi Sarkar, Siddhartha S. Ghosh. Therapeutic targeting of MELK using a drug repurposing approach to combat TNBC cells [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 5978.