Conformational Fluctuations Research Articles

A Computational Approach to Characterize the Protein S-Mer Tyrosine Kinase (PROS1-MERTK) Protein-Protein Interaction Dynamics.

Protein S (PROS1) has recently been identified as a ligand for the TAM receptor MERTK, influencing immune response and cell survival. The PROS1-MERTK interaction plays a role in cancer progression, promoting immune evasion and metastasis in multiple cancers by fostering a tumor-supportive microenvironment. Despite its importance, limited structural insights into this interaction underscore the need for computational studies to explore their binding dynamics, potentially guiding targeted therapies. In this study, we investigated the PROS1-MERTK interaction using advanced computational analyses to support immunotherapy research. High-resolution structural models from ColabFold, an AlphaFold2 adaptation, provided a baseline structure, allowing us to examine the PROS1-MERTK interface with ChimeraX and map residue interactions through Van der Waals criteria. Molecular dynamics (MD) simulations were conducted in GROMACS over 100 ns to assess stability and conformational changes using RMSD, RMSF, and radius of gyration (Rg). The PROS1-MERTK interface was predicted to contain a heterogeneous mix of amino acid contacts, with lysine and leucine as frequent participants. MD simulations demonstrated prominent early structural shifts, stabilizing after approximately 50 ns with small conformational shifts occurring as the simulation completed. In addition, there are various regions in each protein that are predicted to have greater conformational fluctuations as compared to others, which may represent attractive areas to target to halt the progression of the interaction. These insights deepen our understanding of the PROS1-MERTK interaction role in immune modulation and tumor progression, unveiling potential targets for cancer immunotherapy.

Effect of Pregenomic RNA on the Mechanical Stability of HBV Capsid by Coarse-Grained Molecular Simulations.

Hepatitis B virus (HBV) is a double-stranded DNA virus, but its life cycle involves an intermediate stage, during which pregenomic RNA (pgRNA) is encapsulated in the capsid and then reverse-transcribed into the minus DNA strand. These immature HBV virions are the key target for antiviral drug discovery. In this study, we investigate the flexibility and mechanical stability of the HBV capsid containing pgRNA by employing residue-resolved coarse-grained molecular dynamics simulations. The results showed that the presence of pgRNA tends to decrease the overall flexibility of the capsid. In addition, the symmetrically arranged subunits of the capsid show asymmetry in the dominant modes of the conformational fluctuations with or without the presence of pgRNA. Furthermore, the simulations revealed that the presence of pgRNA enhances the overall mechanical stability of the virion particle. Electrostatic interactions between the disordered CTD of capsid and pgRNA were found to play a crucial role in modulating viral mechanical stability. Decreasing the electrostatic interactions by CTD phosphorylation or high salt concentration significantly reduces the mechanical stability of the HBV capsid containing pgRNA. Finally, the 2-fold symmetric sites have been proposed to be the most vulnerable to rupture during the initial stages of capsid disassembly. These findings could enhance our understanding of the physical basis of viral invasion and provide valuable insights into the development of antiviral drugs.

Spectroscopic, DFT and molecular docking studies of novel diosgenin NSAID conjugates and their in vitro evaluation as potential anti-cancer agents against SiHa cells

In the current study, diosgenin-etodolac and diosgenin-naproxen conjugates have been synthesized using Steglich reaction. The synthesized compound 2 and 3 were purified using column chromatography and characterized with the help of modern spectroscopic techniques like 1H, 13C NMR, FT-IR, UV-Visible spectroscopy and mass spectrometry. The geometries of both the compounds were optimized in the ground state by density function theory at the B3LYP/6-31G(d,p) level. These synthesized compounds were evaluated in vitro for their anti-cancer activity against SiHa cells which demonstrated an increased apoptotic activity in comparison to the parent compound i.e. diosgenin. Molecular docking studies were carried out to investigate the inhibitory action of steroidal derivatives against the HPV16 E7 (PDBID- 2B9D) and HPV18 E2 (PDBID- 1F9F) proteins. The result of molecular docking revealed good interactions between compound 2 and 3 with the selected proteins. The computational analysis data and experimental data were in conformation with each other. Molecular simulation was performed for 50ns to access the conformational stability and fluctuation of protein ligand complexes during the simulation.

Computational Exploration of Isatin Derivatives for InhA Inhibition in Tuberculosis: Molecular Docking, MD Simulations and ADMET Insights.

Anti-tubercular drug discovery is a critical research area aimed at addressing the global health burden imposed by Mycobacterium tuberculosis. Nowadays, computational techniques have increased the likelihood of drug development compared to traditional, labor-intensive, and time-consuming drug design approaches. The pivotal goal of drug design is to identify compounds capable of selectively targeting protein, thereby disrupting its enzymatic activity. InhA, or NADH-dependent enoyl-acyl carrier protein reductase, stands at the forefront of targeted approaches in the battle against TB. Isatin derivatives have garnered interest for their diverse pharmacological activities. To identify novel isatin derivatives that could serve as potential chemical templates for anti-TB drug discovery by targeting InhA. The present work utilized various computational approaches, including molecular docking, binding free energy calculations, and conformational alignment studies to investigate the binding mode and interactions of carefully selected dataset of 88 isatin derivatives within InhA active site. Study also employed MD simulations of the most promising molecule to check the stability of the protein-ligand complex and in-silico ADMET profiling of the top compounds to predict their pharmacokinetic and toxicity properties. Results provided insights into the structural features contributing to InhA inhibition, assessing overall drug-like characteristics of isatin derivatives and identified compound 48 (BA= -10.4 kcal mol-1 ) with potential for further optimization. MD simulation analysis revealed that compound 48 binds firmly within the InhA protein, exhibiting minimal conformational fluctuations and enhanced stability. Considering the aforementioned, isatin derivatives represents a novel framework for creating targeted InhA inhibitors during anti-TB therapy. However, experimental validations and in-depth analyses are crucial to confirm efficacy and safety of these derivatives as potential InhA inhibitors for TB treatment.

Deciphering the impact of F23L mutation on the aggregation propensity of human islet amyloid polypeptide using molecular simulations

The self-aggregation of 37-residue human islet amyloid polypeptide (hIAPP) into β-sheet rich oligomers and amyloid fibrils contributes to the loss of pancreatic β-cell mass in type 2 diabetes (T2D). A previous study highlighted that the F23L mutation in the amyloidogenic core (Ser20–Ser29) of hIAPP slows down its self-aggregation by a factor of 2.6. However, the underlying molecular mechanism behind slower aggregation and reduced cytotoxicity of hIAPP on F23L mutation remains obscure. Thus, the structural and conformational changes in F23L–hIAPP that lead to slower aggregation and lower cytotoxicity were examined by molecular dynamics (MD) simulations. The MD simulations depicted that F23L mutation marginally increases the helical content from 10.20 ± 1.94 to 11.50 ± 2.18 % accompanied by a noteworthy decrease in aggregation-prone β-sheet from 14.00 ± 1.58 to 0.80 ± 0.37 %. Notably, FEL conformations depicted a complete disappearance of β-sheet content in F23L–hIAPP as compared to 9–20 % in wt–hIAPP in agreement with the notably reduced toxicity of F23L–hIAPP aggregates against cultured INS-1 832/13 cells. Interestingly, dihedral principal component analysis (dPCA) depicted noteworthy compression in the conformational sub-space and a lower trace value of hIAPP on F23L mutation, which indicates lower conformational fluctuations in F23L–hIAPP. F23L mutation alters the conformational landscape of hIAPP dimer by lowering interchain contacts, and hydrogen bonds as well as reducing binding affinity between chains A-B of hIAPP dimer. Importantly, MD simulations illuminated the key role of Phe23 in mediating intramolecular interactions leading to aggregation-prone structures that promote hIAPP aggregation. The key insights regarding structural transitions and conformational preferences of hIAPP on F23L mutation illuminated from this work will benefit the design and optimization of potential inhibitors targeting Phe23-mediated interactions to block hIAPP aggregation in T2D.

Predicting the Dynamic Interaction of Intrinsically Disordered Proteins.

Intrinsically disordered proteins (IDPs) participate in various biological processes. Interactions involving IDPs are usually dynamic and are affected by their inherent conformation fluctuations. Comprehensive characterization of these interactions based on current techniques is challenging. Here, we present GSALIDP, a GraphSAGE-embedded LSTM network, to capture the dynamic nature of IDP-involved interactions and predict their behaviors. This framework models multiple conformations of IDP as a dynamic graph, which can effectively describe the fluctuation of its flexible conformation. The dynamic interaction between IDPs is studied, and the data sets of IDP conformations and their interactions are obtained through atomistic molecular dynamic (MD) simulations. Residues of IDP are encoded through a series of features including their frustration. GSALIDP can effectively predict the interaction sites of IDP and the contact residue pairs between IDPs. Its performance in predicting IDP interactions is on par with or even better than the conventional models in predicting the interaction of structural proteins. To the best of our knowledge, this is the first model to extend the protein interaction prediction to IDP-involved interactions.

Wet Conformation of Prion-Like Domain and Intimate Correlation of Hydration and Conformational Fluctuations.

Proteins with prion-like domains (PLDs) are involved in neurodegeneration-associated aggregation and are prevalent in liquid-like membrane-less organelles. These PLDs contain amyloidogenic stretches but can maintain dynamic disordered conformations, even in the condensed phase. However, the molecular mechanism underlying such intricate conformational properties of PLDs remains elusive. Here we employed molecular dynamics simulations to investigate the conformational properties of a prototypical PLD system (i.e., FUS PLD). According to our simulation results, PLD adopts a wet collapsed conformation, wherein most residues maintain sufficient hydration with the abundance of internal water. These internal water molecules can rapidly exchange between the protein interior and the bulk, enabling intensive coupling of the entire protein with its hydration environment. The dynamic exchange of water molecules is intimately correlated to the overall conformational fluctuations of PLD. Furthermore, the abundance of dynamic internal water suppresses the formation of aggregation-prone ordered structures. These results collectively elucidate the crucial role of internal water in sustaining the dynamic disordered conformation of the PLD and inhibiting its aggregation propensity.

A molecular synergy of non-covalent interactions facilitated via theobromine modifying the self-assembly process of type I collagen

Type I Collagen is a multifunctional fibrous protein present significantly in the connective tissues. Generally, fibril formation process of an interstitial collagen begins with a triple helix alignment to form a pentafibril, which sequentially self-assembles into a microfibril. Typically, this sequential formation can be achieved under an in vitro condition as well by maintaining certain specific physiological parameters to mimic the interstitial microenvironment of collagen. The necessity to study such a kinetically driven process is due to its implications in template fabrication particularly as a scaffold to enhance the growth of specific stem cells or accelerating nanoparticle synthesis. Drawing inspiration from this, theobromine, a methylxanthine that contributes towards the hydrogen bond network via dimerization and stacking interaction was used as a small molecule in modifying the molecular level interactions of a self-assembled collagen. Initially, rheological studies revealed certain variations in the viscous properties of collagen on addition of theobromine. Turbidity assay showed an increase in the rate of fibril formation and its topographical changes were observed through the high-resolution scanning electron microscope. The stability and probable physico-chemical interactions between collagen and theobromine were comprehended from the vibrational frequency changes recorded using (FT-IR) (ATR) and conformational changes using Circular Dichroism (CD) studies. Our results show possible multibinding sites on theobromine, which would compete to bind with the polar and non-polar residues exposed over the monomeric surfaces of triple helix causing a local conformational fluctuation modifying protein-protein interaction.

Visualizing Single-Molecule Protein Conformational Transitions and Free Energy Landscape.

Monitoring the conformational dynamics of individual proteins is essential to understand the relationship between structure and function in molecular regulatory mechanisms. However, the fast dynamics of single proteins remain poorly understood. Here, we construct a single-molecule sensing platform by introducing plasmonic imaging of single nanoparticles to sense and report the protein conformational changes at the single-molecule level. Tracking the fluctuations of individual nanoparticles with high resolution, we detect and characterize distinct conformational states of molecular chaperone heat shock protein 90 (Hsp90). We also explore the conformational changes of Hsp90 in situ under different nucleotide conditions. Analysis of the conformational fluctuations between the open and closed states of single Hsp90 provides important information on free energy profiles, effective spring constants, and multiphase behaviors. This method offers a strategy to visualize the conformational changes of single proteins in real-time and provides insights into the underlying molecular mechanisms.

Exploring the Impact of C-Terminal Based Pentapeptides on the Disassembly of Aβ42 Fibrils.

An effective therapeutic strategy to suppress Alzheimer's disease (AD) progression is to disrupt β-sheet rich neurotoxic soluble amyloid-β (Aβ) aggregates. Previously, we identified new pentapeptides (RVVPI and RIAPA) with notably enhanced ability to block Aβ42 aggregation as compared to Aβ42 C-terminal derived peptide RIIGL using integrated computational protocol. In this work, the potential of RIIGL, RVVPI, and RIAPA for the structural destabilization of Aβ42 protofibril was assessed by molecular dynamics (MD) simulations and in vitro studies. The binding free energy analysis depicts that charged residues influence Aβ42 protofibril-pentapeptide interactions. Notably, RVVPI displays a more pronounced destabilization effect than other peptides due to higher conformational fluctuations, and disruption of salt bridge (K28-A42) interactions in Aβ42 protofibril. RVVPI exhibited highest inhibitory activity (Inhibition= 66.2%, IC50= 5.57 ± 0.83 µM) against Aβ42 aggregation consistent with computational results. Remarkably, RVVPI displayed ~4.5 fold lower IC50 value as compared to RIIGL. ThT and TEM studies highlighted the enhanced efficiency of RVVPI (62.4%) in the disassembly of pre-formed Aβ42 fibrils than RIIGL and RIAPA. The combined in silico and in vitro studies identified a new peptide, RVVPI, as an efficient inhibitor of Aβ42 fibrillation and disassembly of Aβ42 aggregates.

Molecular Insights into the Conformational and Binding Behaviors of Human Serum Albumin Induced by Surface-Active Ionic Liquids.

Extensive research has been carried out to investigate the stability and function of human serum albumin (HSA) when exposed to surface-active ionic liquids (SAILs) with different head groups (imidazolium, morpholinium, and pyridinium) and alkyl chain lengths (ranging from decyl to tetradecyl). Analysis of the protein fluorescence spectra indicates noticeable changes in the secondary structure of HSA with varying concentrations of all SAILs tested. Helicity calculations based on the Fourier transform infrared (FTIR) data show that HSA becomes more organized at the micellar concentration of SAILs, leading to an increased protein activity at this level. Small-angle neutron scattering (SANS) data confirm the formation of a bead-necklace structure between the SAILs and HSA. Atomistic molecular dynamics (MD) simulation results identify several hotspots on the protein surface for interaction with SAIL, which results in the modulation of protein conformational fluctuation and stability. Furthermore, fluorescence resonance energy transfer (FRET) experiments with the intramolecular charge transfer (ICT) probe trans-ethyl p-(dimethylamino) cinnamate (EDAC) demonstrate that higher alkyl chain lengths and SAIL concentrations result in a significantly increased energy transfer efficiency. The findings of this study provide a detailed molecular-level understanding of how the protein structure and function are affected by the presence of SAILs, with potential implications for a wide range of applications involving protein-SAIL composite systems.

Parsing Dynamics of Protein Backbone NH and Side-Chain Methyl Groups using Molecular Dynamics Simulations.

Experimental NMR spectroscopy and theoretical molecular dynamics (MD) simulations provide complementary insights into protein conformational dynamics and hence into biological function. The present work describes an extensive set of backbone NH and side-chain methyl group generalized order parameters for the Escherichia coli ribonuclease HI (RNH) enzyme derived from 2-μs microsecond MD simulations using the OPLS4 and AMBER-FF19SB force fields. The simulated generalized order parameters are compared with values derived from NMR 15N and 13CH2D spin relaxation measurements. The squares of the generalized order parameters, S2 for the N-H bond vector and Saxis2 for the methyl group symmetry axis, characterize the equilibrium distribution of vector orientations in a molecular frame of reference. Optimal agreement between simulated and experimental results was obtained by averaging S2 or Saxis2 calculated by dividing the simulated trajectories into 50 ns blocks (∼five times the rotational diffusion correlation time for RNH). With this procedure, the median absolute deviations (MAD) between experimental and simulated values of S2 and Saxis2 are 0.030 (NH) and 0.061 (CH3) for OPLS4 and 0.041 (NH) and 0.078 (CH3) for AMBER-FF19SB. The MAD between OPLS4 and AMBER-FF19SB are 0.021 (NH) and 0.072 (CH3). The generalized order parameters for the methyl group symmetry axis can be decomposed into contributions from backbone fluctuations, between-rotamer dihedral angle transitions, and within-rotamer dihedral angle fluctuations. Analysis of the simulation trajectories shows that (i) backbone and side chain conformational fluctuations exhibit little correlation and that (ii) fluctuations within rotamers are limited and highly uniform with values that depend on the number of dihedral angles considered. Low values of Saxis2, indicative of enhanced side-chain flexibility, result from between-rotamer transitions that can be enhanced by increased local backbone flexibility.

Conformational Dynamics of an Amyloidogenic Intermediate of Transthyretin: Implications for Structural Remodeling and Amyloid Formation

The aggregation pathway of transthyretin (TTR) proceeds through rate-limiting dissociation of the tetramer (a dimer of dimers) and partial misfolding of the resulting monomer, which assembles into amyloid structures through a downhill polymerization mechanism. The structural features of the aggregation-prone monomeric intermediate are poorly understood. NMR relaxation dispersion offers a unique opportunity to characterize amyloidogenic intermediates when they exchange on favorable timescales with NMR-visible ground states. Here we use NMR to characterize the structure and conformational dynamics of the monomeric F87E mutant of human TTR. Chemical shifts derived from analysis of multinuclear relaxation dispersion data provide insights into the structure of a low-lying excited state that exchanges with the ground state of the F87E monomer at a rate of 3800 s−1. Disruption of the subunit interfaces of the TTR tetramer leads to destabilization of edge strands in both β-sheets of the F87E monomer. Conformational fluctuations are propagated through the entire hydrogen bonding network of the DAGH β-sheet, from the inner β-strand H, which forms the strong dimer-dimer interface in the TTR tetramer, to outer strand D which is unfolded in TTR fibrils. Fluctuations are also propagated from the AB loop in the weak dimer-dimer interface to the EF helix, which undergoes structural remodeling in fibrils. The conformational fluctuations in both regions are enhanced at acidic pH where amyloid formation is most favorable. The relaxation dispersion data provide insights into the conformational dynamics of the amyloidogenic state of monomeric TTR that predispose it for structural remodeling and progression to amyloid fibrils.

A Practical Guide to All-Atom and Coarse-Grained Molecular Dynamics Simulations Using Amber and Gromacs: A Case Study of Disulfide-Bond Impact on the Intrinsically Disordered Amyloid Beta.

Intrinsically disordered proteins (IDPs) pose challenges to conventional experimental techniques due to their large-scale conformational fluctuations and transient structural elements. This work presents computational methods for studying IDPs at various resolutions using the Amber and Gromacs packages with both all-atom (Amber ff19SB with the OPC water model) and coarse-grained (Martini 3 and SIRAH) approaches. The effectiveness of these methodologies is demonstrated by examining the monomeric form of amyloid-β (Aβ42), an IDP, with and without disulfide bonds at different resolutions. Our results clearly show that the addition of a disulfide bond decreases the β-content of Aβ42; however, it increases the tendency of the monomeric Aβ42 to form fibril-like conformations, explaining the various aggregation rates observed in experiments. Moreover, analysis of the monomeric Aβ42 compactness, secondary structure content, and comparison between calculated and experimental chemical shifts demonstrates that all three methods provide a reasonable choice to study IDPs; however, coarse-grained approaches may lack some atomistic details, such as secondary structure recognition, due to the simplifications used. In general, this study not only explains the role of disulfide bonds in Aβ42 but also provides a step-by-step protocol for setting up, conducting, and analyzing molecular dynamics (MD) simulations, which is adaptable for studying other biomacromolecules, including folded and disordered proteins and peptides.

Synthesis, molecular docking and molecular dynamics simulations, drug-likeness studies, ADMET prediction and biological evaluation of novel pyrazole-carboxamides bearing sulfonamide moiety as potent carbonic anhydrase inhibitors.

Pyrazoles are unique bioactive molecules with a versatile biological profile and they have gained an important place on pharmaceutical chemistry. Pyrazole compounds containing sulfonamide nuclei also attract attention as carbonic anhydrase (CA) inhibitors. In this study, a library of pyrazole-carboxamides were synthesized and the structures of the synthesized molecules were characterized using FT-IR, 1H-NMR, 13C-NMR and HRMS. Then the inhibition effects of newly synthesized molecules on human erythrocyte hCA I and hCA II isoenzymes were investigated. Ki values of the compounds were in the range of 0.063-3.368µM for hCA I and 0.007-4.235µM for hCA II. Molecular docking studies were performed between the most active compounds 6a, 6b and the reference inhibitor, acetazolamide (AAZ) and the hCA I and hCA II receptors to investigate the binding mechanisms between the compounds and the receptors. These compounds showed better interactions than the AAZ. ADMET analyzes were performed for the compounds and it was seen that the compounds did not show AMES toxicity. The stability of the molecular docking results over time was analysed by 50ns molecular dynamics simulations. Molecular dynamics simulations revealed that 6a and 6b exhibited good stability after docking to the binding sites of hCA I and hCA II receptors, with minor conformational changes and fluctuations.

Entropy associated with conformational and solvent-density fluctuations in biomolecular solutions

Microscopic formula to describe the entropy of biomolecular solutions are derived based on the Gibbs formula of entropy, and the generalized Langevin theory combined with the RISM/3D-RISM theory. Two formula are derived: one is concerned with the conformational fluctuation of a biomolecule, and the other with the density fluctuation of solvent around a solute. The formula derived for the entropy associated with the conformational fluctuation is Sconf=12kBlog2π3NA+3N2kBwhere N is the number of atoms in the solute, and A is the determinant of the inverse of the variance–covariance matrix of conformational fluctuation.The formula for the entropy of solvent at a pair of positions around a solute is also derived to be, ssolv(r,r′)=12kBlog2πnB+3n2kBwhere n is the number of atoms in a solvent molecule, and B is essentially the determinant of the matrix of the density-pair-correlation functions. The entropy at a local position r may be obtained by integrating the expression by r′ over the entire volume of the system.The feasibility of the calculation to find the entropies is discussed.

Computational study on the binding mechanism of allosteric drug TNO155 inhibiting SHP2E76A.

E76A mutations of SHP2 have been reported to associate with genetic developmental diseases and cancers, and TNO155 is one of the effective inhibitors targeted to the allosteric site 1, which has already entered the clinical stage. However, the detailed binding mechanism between them still needs further clarification at micro-atomic level. In this study, the binding mechanism of TNO155 inhibiting SHP2E76A and the superiorities of TNO155 at binding affinity and dynamic interactive behavior with SHP2E76A were probed utilizing a series of computational drug design technologies. The results show that SHP2E76A forms tighter interaction with TNO155 compared to SHP099. SHP2E76A-TNO155 exhibits the largest electrostatic interaction among all complex systems, which can be manifested by the strong hydrogen bond interactions formed by two electrically charged residues, Arg111 and Glu250. Notably, in SHP2E76A-TNO155 system, Asp489 makes an additional substantial beneficial contribution. The E76A mutation brings stronger residue positive correlation and a larger conformation fluctuation between N-CH2 and PTP domains, resulting in tighter binding betweenTNO155and SHP2E76A. This study offers valuable insights for the further design and development of novel SHP2E76A allosteric inhibitors.

Nonlinear Impact of Electrolyte Solutions on Protein Dynamics.

Halophilic organisms have adapted to multi-molar salt concentrations, their cytoplasmic proteins functioning despite stronger attraction between hydrophobic groups. These proteins, of interest in biotechnology because of decreasing fresh-water resources, have excess acidic amino acids. It has been suggested that conformational fluctuations - critical for protein function - decrease in the presence of a stronger hydrophobic effect, and that an acidic proteome would counteract this decrease. However, our understanding of the salt- and acidic amino acid dependency of enzymatic activity is limited. Here, using solution NMR relaxation and molecular dynamics simulations for in total 14 proteins, we show that salt concentration has a limited and moreover non-monotonic impact on protein dynamics. The results speak against the conformational-fluctuations model, instead indicating that maintaining protein dynamics to ensure protein function is not an evolutionary driving force behind the acidic proteome of halophilic proteins.

Temperature-Induced Luminescence Intensity Fluctuation of Protein-Protected Copper Nanoclusters: Role of Scaffold Conformation vs Nonradiative Transition.

Protein-scaffolded atomically precise metal nanoclusters (NCs) have emerged as a promising class of biofriendly nanoprobes at the forefront of modern research, particularly in the area of sensing. The photoluminescence (PL) intensity of several nanoclusters showed a systematic temperature-dependent fluctuation, but the mechanism remains ambiguous and is poorly understood. We tried to shed some light on this mechanistic aspect by testing a couple of hypotheses: (i) conformational fluctuation of the protein scaffold-mediated PL intensity fluctuation and (ii) PL intensity fluctuation due to the variation in the radiative and nonradiative transition rates. Herein, the PL intensity of the lysozyme-capped copper nanocluster (Lys-Cu NC) showed excellent temperature dependency; upon increasing the temperature, the PL intensity gradually decreased. However, contrasting effects can be seen when the nanocluster is exposed to a chemical denaturant (guanidine hydrochloride (GdnHCl)); the PL intensity increased with the increase in the GdnHCl concentration due to the change in the ionic strength of the medium. This discrepancy clearly suggests that the thermal PL intensity fluctuation cannot be explained by a change in the scaffold conformation. Furthermore, upon closer investigation, we observed a 2-fold increase in the nonradiative decay rate of the Lys-Cu NC at the elevated temperature, which could reasonably explain the decrease in the PL intensity of the nanocluster at the higher temperature. Additionally, from the result, it was evident that the protein scaffold-metal core interaction played a key role here in stabilizing each other; hence, the scaffold structure remained unaffected even in the presence of chemical denaturants.

Repurposing of antimycobacterium drugs for COVID-19 treatment by targeting SARS CoV-2 main protease: An in-silico perspective

The global mortality rate has been significantly impacted by the COVID-19 pandemic, caused by the SARS CoV-2 virus. Although the pursuit for a potent antiviral is still in progress, experimental therapies based on repurposing of existing drugs is being attempted. One important therapeutic target for COVID-19 is the main protease (Mpro) that cleaves the viral polyprotein in its replication process. Recently minocycline, an antimycobacterium drug, has been successfully implemented for the treatment of COVID-19 patients. But it’s mode of action is still far from clear. Furthermore, it remains unresolved whether alternative antimycobacterium drugs can effectively regulate SARS CoV-2 by inhibiting the enzymatic activity of Mpro. To comprehend these facets, eight well-established antimycobacterium drugs were put through molecular docking experiments. Four of the antimycobacterium drugs (minocycline, rifampicin, clofazimine and ofloxacin) were selected by comparing their binding affinities towards Mpro. All of the four drugs interacted with both the catalytic residues of Mpro (His41 and Cys145). Additionally, molecular dynamics experiments demonstrated that the Mpro-minocyline complex has enhanced stability, experiences reduced conformational fluctuations and greater compactness than other three Mpro-antimycobacterium and Mpro-N3/lopinavir complexes. This research furnishes evidences for implementation of minocycline against SARS CoV-2. In addition, our findings also indicate other three antimycobacterium/antituberculosis drugs (rifampicin, clofazimine and ofloxacin) could potentially be evaluated for COVID-19 therapy.