Free Energy Analysis Research Articles

Linear Free Energy Analysis on the Ring‐Expansion of Arylthiiranes with Ketenes

AbstractThe ring‐expansion of arylthiiranes and phenoxyacetyl chloride was performed in the presence of triethylamine and provided a novel strategy for the synthesis of 4,5‐dihydrobenzo[d]thiepin‐2(1H)‐ones, benzo[d]‐ϵ‐thiolactones, directly without catalysts or additives. Its linear free energy analysis was conducted on the basis of competitive experiments. The results indicate that both reaction constants are close to zero (0.14 for σm and 0.20 for σp), supporting the proposed sulfur‐shifted ene mechanism. The current reaction features atom and step‐economic one‐pot characteristic via a tandem sequence of in situ ketene generation, sulfur‐shifted ene reaction, and aromatization.

Design of Metal Sulfide Electrode for Hydrogen Production by Electrolysis

Hydrogen evolution reaction (HER) is the cathodic hydrogen evolution reaction in electrolytic cell, but the hydrogen evolution catalytic properties of electrode materials best remains is the precious metal catalyst, therefore, in order to study the catalytic performance is good, and cheap hydrogen evolution electrode materials has become the research hot spot, metal sulfide can be mixed and with good electrical conductivity is it can be used as a necessary condition for hydrogen evolution electrode, The core theory of this paper is the first principle. By taking metal sulfide as the matrix and doping it with 10 metal group elements, Sc, Ti, V, Cr, Mn, Fe, Co, Ni, Cu and Zn, we obtained the configuration of 20 metal sulfide by doping it at two different sites of S atom, and inlaid H atom into metal atom. Then, through the use of software to study its catalytic performance, through the free energy analysis, rate analysis, bond length analysis, density of states analysis, charge analysis method, compared and found the most suitable doping metal element V, thus also determined that metal sulfide can be used as hydrogen evolution electrode through metal doping.

Kinetics guided engineering of cyclodextrin glycosyltransferase with enhanced intermolecular transglycosylation activity

AbstractCyclodextrin glycosyltransferase (CGTase) catalyzes intermolecular transglycosylation through either disproportionation or cyclization‐coupling pathway. Kinetics analysis reveals that the hesperidin glycosylation process catalyzed by a CGTase variant (M1) is primarily accomplished through the disproportionation pathway. The cyclization‐coupling pathway exhibits a lower reaction rate and competitively consumes glycosyl donor and yield byproducts that impair disproportionation. Under the guidance of reaction kinetics, mutagenesis was targeted at residues in the −3, +1, and +2 subsites, known to control the selectivity between disproportionation and cyclization. A quadruple variant was identified with 2.9 times hesperidin glycosylation activity compared to M1, and 20.3 times compared to the wild‐type. Kinetic analysis reveals a fourfold improvement of kcat/KmA for disproportionation and an 85.5% reduction in kcat/Km for cyclization after mutagenesis. Binding free energy analysis further confirms that the mutagenesis favors the binding of hesperidin, and destabilizes the binding of cyclodextrin.

Evaluation of the electrochemical interaction in the asphalt emulsion-aggregate system of cold mix asphalt through zeta potential and surface free energy analysis

ABSTRACT The interaction in the emulsion-aggregate system is well known and influences the Cold Mix Asphalt (CMA) performance. However, the electrochemical interaction indexes for the emulsion-aggregate systems are still not well understood. Therefore, the present investigation focussed on evaluating the electrochemical interaction in the Asphalt Emulsion-Aggregate system (AEA-S) of Cold Mix Asphalt (CMA). Zeta Potential (ZP), X-ray diffraction (XRD), and Surface Free Energy (SFE) analysis were carried out in three slow-setting cationic asphalt emulsions and three common Colombian aggregates (alluvial and quarried) to determine the electrical potential and interaction in the emulsion-aggregate system. Zeta Potential analysis shows both dependence on the chemical compounds of the aggregates and variation in pH conditions. Moreover, Zeta Potential shows negative values for all three aggregates in the entire pH range variation and decreases with asphalt emulsions pH associated with SiO 2 / Al 2 O 3 ratio. Through chemical identification and electrokinetic forces is feasible to conclude that high Zeta Potential (ZP) and Surface Free Energy (SFE) values improve the electrochemical ad of the asphalt emulsion-aggregate system (AEA-S), demonstrating that high polarity is an essential factor in Cold Mix Asphalts (CMA).

Unveiling Novel HIV-1 Protease Inhibitors through an Integrated Analysis of 3D-QSAR, Molecular Docking, and Binding Free Energy

Introduction: HIV-1, the primary causative agent of AIDS, remains a formidable and lethal virus globally, claiming the lives of millions over the past four decades since its discovery. Recent research has underscored the potential of HIV-1 protease as a therapeutic target, offering a promising strategy for inhibiting viral replication within the body. Method: In light of this, we have curated an extensive database comprising 193 derivatives of Darunavir (DRV), an HIV-1 protease inhibitor. Simultaneously, we have developed a comprehensive set of 3D-QSAR models to elucidate the structure-activity relationships of these 193 derivative inhibitors. Employing various computational simulation techniques, including Comparative Molecular Field Analysis (CoMFA), Comparative Similarity Indices Analysis (CoMSIA), and molecular docking, we have unveiled the fundamental three-dimensional structural features influencing their biological activity. Result: Results indicate that the optimal CoMSIA model (Q2 = 0.500, R2 ncv = 0.882, R2 pred = 0.797) surpasses other models, demonstrating superior predictive capability. Furthermore, docking results suggest that DRV derivatives maintain stable conformations within the binding cavity due to synergistic interactions, such as hydrogen bonding and non-bonded interactions. Drawing insights from the best computational models, we have designed five DRV derivatives with significant HIV-1 protease inhibitory activity through local modification, with theoretical calculations indicating favorable pharmacokinetic properties and synthetic feasibility for the newly proposed molecules. Conclusion: It is hoped that the findings and conclusions obtained herein may furnish theoretical underpinning and directional guidance for the design, optimization, and experimental synthesis of DRV derivative compounds for pharmaceutical purposes. conclusion: In conclusion, this research identifies key residues, including Asp25, Gly27, Asp29, Asp30, Asp124, and Asp129, as significant for ligand binding. The information derived from the in silico models contributes to the design of five newly proposed DRV derivative compounds as promising HIV-1 protease inhibitors, surpassing the inhibitory activity of compound 171. The study holds potential for optimizing Darunavir derivatives in the development of anti-HIV-1 protease drugs.

An integrated investigation combining network pharmacology and computer simulation dissects the potential mechanism of anti-obesity of Monascus pigments (MPs)

Monascus pigments (MPs), the secondary metabolites of Monascus-fermented foods, have been widely studied for their anti-obesity effects. However, the specific targets and potential mechanism of MPs for anti-obesity remain unclear. In this study, we applied network pharmacology and computer simulation to investigate the anti-obesity potential and action mechanism of MPs. Based on public databases, 117 potential therapeutic obesity targets of MPs were predicted. Five key targets (STAT3, ESR1, BCL2, PPARG, and MMP9) were obtained by protein-protein interaction (PPI) analysis and microarray data validation. The enrichment results showed that MPs exerted anti-obesity effects through multiple targets and multiple pathways, especially insulin resistance. Molecular docking demonstrated the binding of five key targets to MPs ligands through hydrophobic interactions and hydrogen bonding. Molecular dynamics simulation and binding free energy analysis revealed a higher stability in the binding of ESR1, BCL2, and PPARG targets with MPs ligands. In addition, free energy landscape (FEL) and independent gradient model (IGM) analysis showed that van der Waals forces were also the main driving force in stabilizing the binding of key targets and MPs ligands. This study systematically illustrated the potential anti-obesity mechanism of MPs and established the foundation for the development and application of MPs as anti-obesity functional additives.

Structural Studies on the Binding Mode of Bisphenols to PPARγ.

Bisphenol A (BPA) and bisphenol B (BPB) are widely used in the production of plastics, and their potential adverse health effects, particularly on endocrine disruption and metabolic health, have raised concern. Peroxisome proliferator-activated receptor gamma (PPARγ) plays a pivotal role in metabolic regulation and adipogenesis, making it a target of interest in understanding the development of obesity and associated health impacts. In this study, we employ X-ray crystallography and molecular dynamics (MD) simulations to study the interaction of PPARγ with BPA and BPB. Crystallographic structures reveal the binding of BPA and BPB to the ligand binding domain of PPARγ, next to C285, where binding of partial agonists as well as antagonists and inverse agonists of PPARγ signaling has been previously observed. However, no interaction of BPA and BPB with Y437 in the activation function 2 site is observed, showing that these ligands cannot stabilize the active conformation of helix 12 directly. Furthermore, free energy analyses of the MD simulations revealed that I341 has a large energetic contribution to the BPA and BPB binding modes characterized in this study.

An in silico approach to identify novel and potential Akt1 (protein kinase B-alpha) inhibitors as anticancer drugs.

Akt1 (protein kinase B) has become a major focus of attention due to its significant functionality in a variety of cellular processes and the inhibition of Akt1 could lead to a decrease in tumour growth effectively in cancer cells. In the present work, we discovered a set of novel Akt1 inhibitors by using multiple computational techniques, i.e. pharmacophore-based virtual screening, molecular docking, binding free energy calculations, and ADME properties. A five-point pharmacophore hypothesis was implemented and validated with AADRR38. The obtained R2 and Q2 values are in the acceptable region with the values of 0.90 and 0.64, respectively. The generated pharmacophore model was employed for virtual screening to find out the potential Akt1 inhibitors. Further, the selected hits were subjected to molecular docking, binding free energy analysis, and refined using ADME properties. Also, we designed a series of 6-methoxybenzo[b]oxazole analogues by comprising the structural characteristics of the hits acquired from the database. Molecules D1-D10 were found to have strong binding interactions and higher binding free energy values. In addition, Molecular dynamic simulation was performed to understand the conformational changes of protein-ligand complex.

Alpha-cyperone mitigates renal ischemic injury via modulation of HDAC-2 expression in diabetes: Insights from molecular dynamics simulations and experimental evaluation

Chronic diabetes mellitus is reported to be associated with acute kidney injury. The enzyme histone deacetylase-2 (HDAC-2) was found to be upregulated in diabetes-related kidney damage. Alpha-cyperone (α-CYP) is one of the active ingredients of Cyperus rotundus that possesses antioxidant and anti-inflammatory effects. We evaluated the effect of α-CYP on improving oxidative stress and tissue inflammation following renal ischemia/reperfusion (I/R) injury in diabetic rats. The effect of α-CYP on HDAC-2 expression in renal homogenates and in the NRK-52 E cell line was evaluated following renal I/R injury and high glucose conditions, respectively. Molecular docking was used to investigate the binding of α-CYP with the HDAC-2 active site. Both renal function and oxidative stress were shown to be impaired in diabetic rats due to renal I/R injury. Significant improvements in kidney/body weight ratio, creatinine clearance, serum creatinine, blood urea nitrogen (BUN), and uric acid were observed in diabetic rats treated with α-CYP (50 mg/kg) two weeks prior to renal I/R injury. α-CYP treatment also improved histological alterations in renal tissue and lowered levels of malondialdehyde, myeloperoxidase, and hydroxyproline. Treatment with α-CYP suppressed the increased HDAC-2 expression in the renal tissue of diabetic rats and in the NRK-52 E cell line. The molecular docking reveals that α-CYP binds to HDAC-2 with good affinity, ascertained by molecular dynamics simulations and binding free energy analysis. Overall, our data suggest that α-CYP can effectively prevent renal injury in diabetic rats by regulating oxidative stress, tissue inflammation, fibrosis and inhibiting HDAC-2 activity.

Exploring the activation mechanism of metabotropic glutamate receptor 2

Homomeric dimerization of metabotropic glutamate receptors (mGlus) is essential for the modulation of their functions and represents a promising avenue for the development of novel therapeutic approaches to address central nervous system diseases. Yet, the scarcity of detailed molecular and energetic data on mGlu2 impedes our in-depth comprehension of their activation process. Here, we employ computational simulation methods to elucidate the activation process and key events associated with the mGlu2, including a detailed analysis of its conformational transitions, the binding of agonists, Gi protein coupling, and the guanosine diphosphate (GDP) release. Our results demonstrate that the activation of mGlu2 is a stepwise process and several energy barriers need to be overcome. Moreover, we also identify the rate-determining step of the mGlu2's transition from the agonist-bound state to its active state. From the perspective of free-energy analysis, we find that the conformational dynamics of mGlu2's subunit follow coupled rather than discrete, independent actions. Asymmetric dimerization is critical for receptor activation. Our calculation results are consistent with the observation of cross-linking and fluorescent-labeled blot experiments, thus illustrating the reliability of our calculations. Besides, we also identify potential key residues in the Gi protein binding position on mGlu2, mGlu2 dimer's TM6-TM6 interface, and Gi α5 helix by the change of energy barriers after mutation. The implications of our findings could lead to a more comprehensive grasp of class C G protein-coupled receptor activation.

Efficient desalination in fluorinated multilayered covalent organic framework: Tunning the energy landscape inside the nanochannel

The design and construction of advanced nanochannels can significantly enhance the performance of reverse osmosis (RO) membranes in desalination, offering potential solutions to the severe freshwater shortage crisis. In this study, we investigated the desalination performance of nanochannels formed by multilayered covalent organic frameworks (COF) that had undergone various types of chemical functionalization, through nonequilibrium molecular dynamics simulations. Our data reveals that fluorination of the nanochannel results in the most impressive desalination performance, as evidenced by significant improvements in both water permeability (increasing from 39.1 to 100.1 L cm−2 day−1 MPa−1) and salt rejection (rising from 91.9 % to 97.1 %). Especially, in multilayered systems, fluorinated nanochannel mitigates the typical decline in water permeability with increasing membrane thickness. For the working mechanism, the free energy analysis indicates that fluorination contributes to a smooth energy landscape for water molecules inside the nanochannel, reducing their interaction with the nanochannel, which results in a more dispersed arrangement of water molecules with fewer hydrogen bonds and a significantly enhanced water velocity, thus facilitating their fast and unobstructed permeation. Therefore, this study offers a promising semipermeable membrane for high-efficiency desalination, achieved through fluorination. It also demonstrates an indicative approach for advanced channel design through fluorination engineering.

Study on β-glucosidase activators by 3D-QSAR, molecular docking and molecular dynamics simulation

To investigate the conformational relationship and mechanism of action of β-glucosidase (BGL) activators, a theoretical study of three-dimensional quantitative structure activity relationship, molecular docking, molecular dynamics (MD) simulations, and binding free energy analysis were performed. The results indicate that comparative molecular field analysis (CoMFA) and comparative molecular similarity index analysis (CoMSIA) models had good stability and predictive ability, with r2cv/ r2pred values of 0.540/0.998 and 0.654/0.993, respectively. The derived contour maps of steric, electrostatic, and hydrogen bond donor field further displayed the modified information of these activators. Molecular docking and MD were performed on calcium diascorbate (CaAS) and L-Ascorbyl 2,6-Dipalmitate (L-ADP), which have good activating ability. The study indicates a positive interaction between the activators and the enzyme, and this interaction does not cause irreversible negative effects on the conformation of BGL. The MD results show that the total binding free energies of CaAS and L-ADP with BGL were −19.837 kJ/mol and −37.798 kJ/mol, respectively, and the binding force of the activators with BGL was mainly derived from hydrophobic interaction and hydrogen bonding. This study offers important guidance for the efficient use of BGL and for the research and development of effective activators.

Ionic Liquid Gating Induces Anomalous Permeation through Membrane Channel Proteins.

Membrane channel proteins (MCPs) play key roles in matter transport through cell membranes and act as major targets for vaccines and drugs. For emerging ionic liquid (IL) drugs, a rational understanding of how ILs affect the structure and transport function of MCP is crucial to their design. In this work, GPU-accelerated microsecond-long molecular dynamics simulations were employed to investigate the modulating mechanism of ILs on MCP. Interestingly, ILs prefer to insert into the lipid bilayer and channel of aquaporin-2 (AQP2) but adsorb on the entrance of voltage-gated sodium channels (Nav). Molecular trajectory and free energy analysis reflect that ILs have a minimal impact on the structure of MCPs but significantly influence MCP functions. It demonstrates that ILs can decrease the overall energy barrier for water through AQP2 by 1.88 kcal/mol, whereas that for Na+ through Nav is increased by 1.70 kcal/mol. Consequently, the permeation rates of water and Na+ can be enhanced and reduced by at least 1 order of magnitude, respectively. Furthermore, an abnormal IL gating mechanism was proposed by combining the hydrophobic nature of MCP and confined water/ion coordination effects. More importantly, we performed experiments to confirm the influence of ILs on AQP2 in human cells and found that treatment with ILs significantly accelerated the changes in cell volume in response to altered external osmotic pressure. Overall, these quantitative results will not only deepen the understanding of IL-cell interactions but may also shed light on the rational design of drugs and disease diagnosis.

Exploring Binding Pockets in the Conformational States of the SARS-CoV-2 Spike Trimers for the Screening of Allosteric Inhibitors Using Molecular Simulations and Ensemble-Based Ligand Docking.

Understanding mechanisms of allosteric regulation remains elusive for the SARS-CoV-2 spike protein, despite the increasing interest and effort in discovering allosteric inhibitors of the viral activity and interactions with the host receptor ACE2. The challenges of discovering allosteric modulators of the SARS-CoV-2 spike proteins are associated with the diversity of cryptic allosteric sites and complex molecular mechanisms that can be employed by allosteric ligands, including the alteration of the conformational equilibrium of spike protein and preferential stabilization of specific functional states. In the current study, we combine conformational dynamics analysis of distinct forms of the full-length spike protein trimers and machine-learning-based binding pocket detection with the ensemble-based ligand docking and binding free energy analysis to characterize the potential allosteric binding sites and determine structural and energetic determinants of allosteric inhibition for a series of experimentally validated allosteric molecules. The results demonstrate a good agreement between computational and experimental binding affinities, providing support to the predicted binding modes and suggesting key interactions formed by the allosteric ligands to elicit the experimentally observed inhibition. We establish structural and energetic determinants of allosteric binding for the experimentally known allosteric molecules, indicating a potential mechanism of allosteric modulation by targeting the hinges of the inter-protomer movements and blocking conformational changes between the closed and open spike trimer forms. The results of this study demonstrate that combining ensemble-based ligand docking with conformational states of spike protein and rigorous binding energy analysis enables robust characterization of the ligand binding modes, the identification of allosteric binding hotspots, and the prediction of binding affinities for validated allosteric modulators, which is consistent with the experimental data. This study suggested that the conformational adaptability of the protein allosteric sites and the diversity of ligand bound conformations are both in play to enable efficient targeting of allosteric binding sites and interfere with the conformational changes.

Cheminformatics approach to identify andrographolide derivatives as dual inhibitors of methyltransferases (nsp14 and nsp16) of SARS-CoV-2

The Covid-19 pandemic outbreak has accelerated tremendous efforts to discover a therapeutic strategy that targets severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) to control viral infection. Various viral proteins have been identified as potential drug targets, however, to date, no specific therapeutic cure is available against the SARS-CoV-2. To address this issue, the present work reports a systematic cheminformatic approach to identify the potent andrographolide derivatives that can target methyltransferases of SARS-CoV-2, i.e. nsp14 and nsp16 which are crucial for the replication of the virus and host immune evasion. A consensus of cheminformatics methodologies including virtual screening, molecular docking, ADMET profiling, molecular dynamics simulations, free-energy landscape analysis, molecular mechanics generalized born surface area (MM-GBSA), and density functional theory (DFT) was utilized. Our study reveals two new andrographolide derivatives (PubChem CID: 2734589 and 138968421) as natural bioactive molecules that can form stable complexes with both proteins via hydrophobic interactions, hydrogen bonds and electrostatic interactions. The toxicity analysis predicts class four toxicity for both compounds with LD50 value in the range of 500–700 mg/kg. MD simulation reveals the stable formation of the complex for both the compounds and their average trajectory values were found to be lower than the control inhibitor and protein alone. MMGBSA analysis corroborates the MD simulation result and showed the lowest energy for the compounds 2734589 and 138968421. The DFT and MEP analysis also predicts the better reactivity and stability of both the hit compounds. Overall, both andrographolide derivatives exhibit good potential as potent inhibitors for both nsp14 and nsp16 proteins, however, in-vitro and in vivo assessment would be required to prove their efficacy and safety in clinical settings. Moreover, the drug discovery strategy aiming at the dual target approach might serve as a useful model for inventing novel drug molecules for various other diseases.

In silico study on graphene quantum dots modified with various functional groups inhibiting α‑synuclein dimerization

Hypothesis: Graphene quantum dots (GQDs) with various functional groups are hypothesized to inhibit the α-synuclein (αS) dimerization, a crucial step in Parkinson’s disease pathogenesis. The potential of differently functionalized GQDs is systematically explored.Experiments: All-atom replica-exchange molecular dynamics simulations (accumulating to 75.6 μs) in explicit water were performed to study the dimerization of the αS non-amyloid component region and the influence of GQDs modified with various functional groups. Conformation ensemble, binding behavior, and free energy analysis were conducted.Findings: All studied GQDs inhibit β-sheet and backbone hydrogen bond formation in αS dimers, leading to looser oligomeric conformations. Charged GQDs severely impede the growth of extended β-sheets by providing extra contact surface. GQD binding primarily disrupts αS inter-peptide interactions through π-π stacking, CH-π interactions, and for charged GQDs, additionally through salt-bridge and hydrogen bonding interactions. GQD-COO– showed the most optimal inhibitory effect, binding mode, and intensity, which holds promise for the development of nanomedicines targeting amyloid aggregation in neurodegenerative diseases.

Experimental and simulation study on the solubility of 1-naphthylamine in twelve neat solvents

To meet the demand of separating and purifying 1-naphthylamine from the reaction production and filling the solubility data gap, the solubility of 1-naphthylamine in twelve pure solvents (acetone, acetonitrile, ethyl acetate, n-butyl acetate, cyclohexane, n-heptane, methanol, ethanol, n-propanol, iso-propanol, n-butanol, and iso-butanol) was experimentally investigated in the range from 273.15 K to 308.15 K. It was found that the solubility of 1-naphthylamine increases markedly with increasing temperature in all solvent systems. The maximum solubility was 0.8978 (in the solvent of acetone,T = 308.15 K) and the minimum solubility was 0.005485 (in the solvent of n-heptane, T = 273.15 K). Then the experimental solubility data was correlated by the modified Apelblat model, Van't Hoff model, NRTL model, Wilson model, and Margules model. ARD% was calculated to assess the accuracy of the five equations and the results indicated that the modified Apelblat model fits optimally with an average ARD% value of 1.62 %. The effects of various physicochemical properties such as solvent polarity, hydrogen bond donor, hydrogen bond acceptor, and cohesive energy density on solute dissolution behavior were explored. In addition, the apparent thermodynamic properties of 1-naphthylamine in different solvents were analyzed based on modified Van’t Hoff model, which indicated the dissolution process of 1-naphthylamine in selected solvents is endothermic and entropy-driving. Finally, the effect of intermolecular interactions on the dissolution behavior was investigated at the molecular scale through molecular dynamics simulation studies, including molecular electrostatic potential surface, solvation free energy and radial distribution function analysis. This work will provide a fundamental guidance for the crystallization, separation, and purification of 1-naphthylamine.

Discovery of a novel SHP2 allosteric inhibitor using virtual screening, FMO calculation, and molecular dynamic simulation.

SHP2 is a non-receptor protein tyrosine phosphatase to remove tyrosine phosphorylation. Functionally, SHP2 is an essential bridge to connect numerous oncogenic cell-signaling cascades including RAS-ERK, PI3K-AKT, JAK-STAT, and PD-1/PD-L1 pathways. This study aims to discover novel and potent SHP2 inhibitors using a hierarchical structure-based virtual screening strategy that combines molecular docking and the fragment molecular orbital method (FMO) for calculating binding affinity (referred to as the Dock-FMO protocol). For the SHP2 target, the FMO method prediction has a high correlation between the binding affinity of the protein-ligand interaction and experimental values (R2 = 0.55), demonstrating a significant advantage over the MM/PBSA (R2 = 0.02) and MM/GBSA (R2 = 0.15) methods. Therefore, we employed Dock-FMO virtual screening of ChemDiv database of ∼2,990,000 compounds to identify a novel SHP2 allosteric inhibitor bearing hydroxyimino acetamide scaffold. Experimental validation demonstrated that the new compound (E)-2-(hydroxyimino)-2-phenyl-N-(piperidin-4-ylmethyl)acetamide (7188-0011) effectively inhibited SHP2 in a dose-dependent manner. Molecular dynamics (MD) simulation analysis revealed the binding stability of compound 7188-0011 and the SHP2 protein, along with the key interacting residues in the allosteric binding site. Overall, our work has identified a novel and promising allosteric inhibitor that targets SHP2, providing a new starting point for further optimization to develop more potent inhibitors. All the molecular docking studies were employed to identify potential leads with Maestro v10.1. The protein-ligand binding affinities of potential leads were further predicted by FMO calculations at MP2/6-31G* level using GAMESS v2020 system. MD simulations were carried out with AmberTools18 by applying the FF14SB force field. MD trajectories were analyzed using VMD v1.9.3. MM/GB(PB)SA binding free energy analysis was carried out with the mmpbsa.py tool of AmberTools18. The docking and MD simulation results were visualized through PyMOL v2.5.0.

Synthesis, Antimicrobial Activities, and Molecular Modeling Studies of Agents for the Sortase A Enzyme.

Sortase A (SrtA) is an attractive target for developing new anti-infective drugs that aim to interfere with essential virulence mechanisms, such as adhesion to host cells and biofilm formation. Herein, twenty hydroxy, nitro, bromo, fluoro, and methoxy substituted chalcone compounds were synthesized, antimicrobial activities and molecular modeling strategies against the SrtA enzyme were investigated. The most active compounds were found to be T2, T4, and T19 against Streptococcus mutans (S. mutans) with MIC values of 1.93, 3.8, 3.94 μg/mL, and docking scores of -6.46, -6.63, -6.73 kcal/mol, respectively. Also, these three active compounds showed better activity than the chlorohexidine (CHX) (MIC value: 4.88 μg/mL, docking score: -6.29 kcal/mol) in both in vitro and in silico. Structural stability and binding free energy analysis of S.mutans SrtA with active compounds were measured by molecular dynamic (MD) simulations throughout 100 nanoseconds (ns) time. It was observed that the stability of the critical interactions between these compounds and the target enzyme was preserved. To prove further, in vivo biological evaluation studies could be conducted for the most promising precursor compounds T2, T4, and T19, and it might open new avenues to the discovery of more potent SrtA inhibitors.

Prediction of deleterious non-synonymous SNPs of TMPRSS2 protein combined with Molecular Dynamics Simulations and free energy analysis to identify the potential peptide substrates against SARS-CoV-2.

Globally the SARS-CoV-2 viral infection demands for the new drugs, the TMPRSS2 target plays a vital role in facilitating the virus entry. The aim of the present study is to identify the potential peptide substrate from the Anti-viral database against TMPRSS2 of SARS-CoV-2. The compound screening and variation analysis were performed using molecular docking analysis and online tools such as PROVEAN and SNAP2 server, respectively. The re-docked crystal structure peptide substrate exhibits -128.151 kcal/mol whereas the RRKK peptide substrate shows -134.158 kcal/mol. Further, the selected compounds were proceeded with Molecular Dynamics Simulation, it explores the stability of the complex by revealing the hotspot residues (His296 and Ser441) were active for nucleophilic attack against TMPRSS2. The average Binding Free Energy values computed through MM/GBSA for RRKK, Camostat, and Crystal Structure were shown -69.9278 kcal/mol, -64.5983 kcal/mol, and -63.9755 kcal/mol, respectively against TMPRSS2. The 'rate of acylation' emerges as an indicator for RRKK's efficacy, it maintains the distance of 3.2 Å with Ser441 resembles, whilst its -NH backbone stabilizes at 2.5 Å 'Michaelis Complex' which leads to prevent the entry of SARS-CoV-2 to human cells. The sequence variation analysis explores that the V160 and G6 substitutions are essential to emphasize the uncover possibilities for the ongoing drug discovery research. Therefore, the identified peptide substrate found to be potent against SARS-CoV-2 and these results will be valuable for ongoing drug discovery research.Communicated by Ramaswamy H. Sarma.