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Polyacetylene (PA) compounds, as natural products, exhibit remarkable properties and distinctive chemical activities. Three structurally similar C14-PA compounds—Echinophorin D, Echinophorin B, and Echinophorin A—extracted from plants demonstrate varying biological activities on the Transient Receptor Potential Channel A1 (TRPA1) protein, which belongs to the TRP (Transient Receptor Potential) family. In the current study, we investigated the binding modes of these three PA compounds with TRPA1 using molecular dynamics (MD), molecular docking, binding free energy calculations, and quantum mechanics/molecular mechanics (QM/MM) methods. Initially, a putative binding site (site-II) in TRPA1 was identified for these compounds; Echinophorin B was found to stabilize the upward A-loop of TRPA1, which is critical for its activation. Furthermore, the binding affinity calculations of PA compounds through molecular fragment decomposition indicate that the arrangement of two triple bonds and one double bond in C14-PA compounds is vital for regulating TRPA1 bioactivity. Additionally, the lipophilic and electronic properties of the three molecules were analyzed in relation to binding affinity, establishing a correlation between TRPA1 activity and these molecular properties. [ABSTRACT FROM AUTHOR]

Diabetes mellitus is a chronic metabolic disorder affecting millions of people worldwide and causes serious complications such as diabetic nephropathy. Curcumin, a natural polyphenol derived from turmeric, has demonstrated antidiabetic, anti‐inflammatory, and antioxidant properties. However, the molecular mechanisms underlying curcumin's anti‐diabetic effects remain incompletely understood. This study employed network pharmacology, molecular docking, and simulation techniques to explore the potential targets, and key pathways of curcumin in the treatment of diabetes. Using SwissTarget prediction and Superpred databases, we predicted the molecular targets for curcumin, while diabetes‐associated genes were obtained from DisGeNet. We identified 60 common targets for curcumin in diabetes. Protein‐protein interaction (PPI) analysis revealed three sub‐networks and ten hub genes with AKT1, TNF‐α, EGFR, and STAT3 identified as key hub genes that could serve as potential biomarkers. Gene enrichment analysis indicated that these genes primarily regulate insulin resistance and other metabolic pathways. Quantum‐polarized ligand docking (QPLD) showed that curcumin establishes multiple hydrogen and hydrophobic interactions with the essential amino acids of these hub targets. Molecular simulation results demonstrated stable dynamic behavior, a compact structure, and variations in residue flexibility. Binding free energy calculations using MM/GBSA and MM/PBSA methods validate curcumin's strong binding to the potential targets. Total binding free energy using MM/GBSA ranged from −21.35 to −30.94 kcal/mol while MM/PBSA calculations showed total binding free energy values between −19.80 and −26.66 kcal/mol. Altogether, this study provides valuable insights into the molecular targets of curcumin in diabetes and lays the foundation for future advancements in diabetes treatment. [ABSTRACT FROM AUTHOR]

Nickel tetraphenyl‐porphyrin (NiTPPH₂) and zinc tetra(4‐methophenyl)‐porphyrin (ZnTPPH₂(p‐methyl)) were successfully synthesized and characterized using 1H NMR spectroscopy. Their antioxidant activities and interactions with the superoxide anion radical (O2•_) were evaluated using cyclic voltammetry. Remarkably, NiTPPH₂ displayed superior antioxidant activity with an IC50 value of 54.57 μg mL−1, significantly outperforming α‐tocopherol (IC50 = 353.27 μg mL−1), indicating its potential as a potent antioxidant. Binding free energy calculations demonstrated that electrostatic interactions predominantly govern the binding, with values of −23.47 kJ mol−1 for NiTPPH₂ and −22.50 kJ mol−1 for ZnTPPH₂(p‐methyl). These values suggest robust binding affinities with O2•_. Quantum chemical parameters, obtained through density functional theory (DFT), showed a strong correlation with experimental results, validating the computational approach. Additionally, ADMET (Absorption, Distribution, Metabolism, Excretion, and Toxicity) and drug‐likeness assessments, alongside molecular docking studies, highlighted favorable pharmacokinetic profiles and binding affinities. These findings underscore the potential of NiTPPH₂ and ZnTPPH₂(p‐methyl) as promising candidates for antioxidant therapy, exhibiting drug‐like properties and favorable pharmacokinetics. This research advances the understanding of these porphyrin derivatives and their application in the development of novel antioxidant therapeutics. [ABSTRACT FROM AUTHOR]

In cancer immunotherapy, the design and optimisation of bispecific antibodies hold great promise. Bispecific T-cell engager (BiTE) antibodies targeting CD3 and CD117/c-kit have shown significant potential in experimental settings. Nevertheless, knowledge on their stable docked conformations at molecular level is still limited. This study presents an approach of employing modified heated coarse-grained molecular dynamics (CGMD) simulations to elucidate the stable docked conformations of BiTE antibodies against CD3 and CD117/c-kit. We integrated molecular dynamics simulation with coarse-grained and temperature control to explore the conformational landscape of these complex interactions. The modified heated CGMD simulation aimed to re-assess the docked poses suggested by ClusPro webserver. Furthermore, the all-atomic trajectories unveiled the dynamic residues formed throughout the simulation process. The per-residue-energy-binding emphasised the crucial amino acids involved in binding within the complex especially between the complementarity-determining regions (CDR) of BiTEs and residues located at the N-terminal of CD117/c-kit and the C-terminal of CD3. The formation of three types of interactions, such as hydrogen bonds, salt-bridge contact and hydrophobic interactions plays a crucial role in the motion, configuration and the free energy landscape of the complexes. This method is a valuable tool for rational drug design especially in the field of cancer immunotherapy. [ABSTRACT FROM AUTHOR]

In binding free energy calculations, simulations must sample all relevant conformations of the system in order to obtain unbiased results. For instance, different ligands can bind to different metastable states of a protein, and if these protein conformational changes are not sampled in relative binding free energy calculations, the contribution of these states to binding is not accounted for and thus calculated binding free energies are inaccurate. In this work, we investigate the impact of different beta‐sectretase 1 (BACE1) protein conformations obtained from x‐ray crystallography on the binding of BACE1 inhibitors. We highlight how these conformational changes are not adequately sampled in typical molecular dynamics simulations. Furthermore, we show that insufficient sampling of relevant conformations induces substantial error in relative binding free energy calculations, as judged by a variation in calculated relative binding free energies up to 2 kcal/mol depending on the starting protein conformation. These results emphasize the importance of protein conformational sampling and pose this BACE1 system as a challenge case for further method development in the area of enhanced protein conformational sampling, either in combination with binding calculations or as an endpoint correction. [ABSTRACT FROM AUTHOR]

Peroxyacid synthesis is the first step in Prilezhaev epoxidation, which is an industrial method to form epoxides. Motivated by the development of a kinetic model as a tool for solvent selection, the effect of solvent type and acid chain length on the lipase‐catalyzed peroxyacid synthesis was studied. A thermodynamic activity‐based ping‐pong kinetic expression was successfully applied to predict the effect of the reagent loadings in hexane. The activity‐based reaction quotients provided a prediction of solvent‐independent equilibrium constants. However, this strategy did not achieve satisfactory estimations of initial rates in solvents of higher polarity. The lack of compliance with some assumptions of this methodology could be confirmed through molecular dynamics calculations i.e. independent solvation energies and lack of solvent interaction with the active site. A novel approach is proposed combining the activity‐based kinetic expression and the free binding energy of the solvent with the active site to predict kinetics upon solvent change. Di‐isopropyl ether generated a strong interaction with the enzyme's active site, which was detrimental to kinetics. On the other hand, toluene or limonene gave moderate interaction with the active site rendering improved catalytic yield compared with less polar solvents, a finding sharpened when peroctanoic acid was produced. [ABSTRACT FROM AUTHOR]

Bromodomain-containing protein 9 (BRD9) is a key player in chromatin remodeling and gene expression regulation, and it is closely associated with the development of various diseases, including cancers. Recent studies have indicated that inhibition of BRD9 may have potential value in the treatment of certain cancers. Molecular dynamics (MD) simulations, Markov modeling and principal component analysis were performed to investigate the binding mechanisms of allosteric inhibitor POJ and orthosteric inhibitor 82I to BRD9 and its allosteric regulation. Our results indicate that binding of these two types of inhibitors induces significant structural changes in the protein, particularly in the formation and dissolution of α-helical regions. Markov flux analysis reveals notable changes occurring in the α-helicity near the ZA loop during the inhibitor binding process. Calculations of binding free energies reveal that the cooperation of orthosteric and allosteric inhibitors affects binding ability of inhibitors to BRD9 and modifies the active sites of orthosteric and allosteric positions. This research is expected to provide new insights into the inhibitory mechanism of 82I and POJ on BRD9 and offers a theoretical foundation for development of cancer treatment strategies targeting BRD9. [ABSTRACT FROM AUTHOR]

Inhibiting MDM2-p53 interaction is considered an efficient mode of cancer treatment. In our current study, Gaussian-accelerated molecular dynamics (GaMD), deep learning (DL), and binding free energy calculations were combined together to probe the binding mechanism of non-peptide inhibitors K23 and 0Y7 and peptide ones PDI6W and PDI to MDM2. The GaMD trajectory-based DL approach successfully identified significant functional domains, predominantly located at the helixes α2 and α2', as well as the β-strands and loops between α2 and α2'. The post-processing analysis of the GaMD simulations indicated that inhibitor binding highly influences the structural flexibility and collective motions of MDM2. Calculations of molecular mechanics–generalized Born surface area (MM-GBSA) and solvated interaction energy (SIE) not only suggest that the ranking of the calculated binding free energies is in agreement with that of the experimental results, but also verify that van der Walls interactions are the primary forces responsible for inhibitor–MDM2 binding. Our findings also indicate that peptide inhibitors yield more interaction contacts with MDM2 compared to non-peptide inhibitors. Principal component analysis (PCA) and free energy landscape (FEL) analysis indicated that the piperidinone inhibitor 0Y7 shows the most pronounced impact on the free energy profiles of MDM2, with the piperidinone inhibitor demonstrating higher fluctuation amplitudes along primary eigenvectors. The hot spots of MDM2 revealed by residue-based free energy estimation provide target sites for drug design toward MDM2. This study is expected to provide useful theoretical aid for the development of selective inhibitors of MDM2 family members. [ABSTRACT FROM AUTHOR]

Tuberculosis, one of the most ancient and formidable infectious diseases, primarily arises from the pathogenic bacterium Mycobacterium tuberculosis (Mtb). Phosphoenolpyruvate carboxykinase (Pck), a potential drug target, is essential for the growth of Mtb that involves in the pathway of gluconeogenesis at the centre of phosphoenolpyruvate-pyruvate-oxaloacetate node. This study aims to understand drug-like properties of the compounds derived from artemisinin, and to investigate their inhibitory roles against Mtb. Molecular docking was performed on a set of 56 artemisinin compounds to identify their binding efficacy to the Mtb protein target. Subsequently, the selected top three complexes were subjected to molecular dynamics simulations. By the trajectory analysis, root mean square deviation and radius of gyration indicated the compactness of the systems without much fluctuation. The principal component analysis revealed that the complexes were less dynamic and energetically more favourable, and Gibbs energy landscape revealed the favourable energetic transitions between conformations. The artemisinin dimer primary alcohol holding good bioavailability scores appears highly stable in complex with Pck (MM/GBSA of −37.67 kcal/mol) that stands as a potential inhibitor of the Mtb target. However, further preclinical experiments and investigations are necessary to evaluate the intrinsic properties and to confirm effectiveness of the drug candidate. [ABSTRACT FROM AUTHOR]

The constraints imposed by natural antibody affinity maturation often culminate in antibodies with suboptimal binding affinities, thereby limiting their therapeutic efficacy. As such, the augmentation of antibody binding affinity is pivotal for the advancement of efficacious antibody-based therapies. Classical experimental paradigms for antibody engineering are financially and temporally prohibitive due to the extensive combinatorial space of sequence variations in the complementarity-determining regions (CDRs). The advent of computational techniques presents a more expeditious and economical avenue for the systematic design and optimization of antibodies. In this investigation, we assess the performance of AlphaFold2 coupled with the binder hallucination technique for the computational refinement of antibody sequences to elevate the binding affinity of pre-existing antigen-antibody complexes. These methodologies exhibit the capability to predict protein tertiary structures with remarkable fidelity, even in the absence of empirically derived data. Our results intimate that the proposed approach is adept at designing antibodies with improved affinities for antigen-antibody complexes unrepresented in AlphaFold2's training dataset, underscoring its potential as a robust and scalable strategy for antibody engineering. [ABSTRACT FROM AUTHOR]

Obesity, a prevalent global health concern, is characterized by excessive fat accumulation, which confers significant nutritional and health risks, including a shortened lifespan and diminished wellbeing. Central to the regulation of energy balance and food intake is the fat mass and obesity-associated (FTO) protein, which modulates the interplay between caloric consumption and energy expenditure. Given its pivotal role in obesity regulation, the identification of effective inhibitors targeting the FTO protein is imperative for developing therapeutic interventions. Currently available anti-obesity drugs are often plagued by undesirable side effects. In contrast, natural plant-derived bioactive compounds are gaining prominence in the pharmaceutical industry due to their efficacy and lower incidence of adverse effects. Little Millet, a traditional cereal known for its rich nutritional profile and high satiety index, was investigated in this study using molecular docking and dynamics simulation approach for its potential as an anti-obesity agent. Our research demonstrates that four bioactive compounds from Little Millet exhibit superior binding energies ranging from 7.22 to 8.83 kcal/mol, compared to the standard anti-obesity drug, orlistat, which has a binding energy of 5.96 kcal/mol. These compounds fulfilled all drug-like criteria, including the Lipinski, Ghose, Veber, Egan, and Muegge rules, and exhibited favorable profiles in terms of distribution, metabolism, and prolonged half-life without toxicity. Conversely, orlistat was associated with hepatotoxicity, a reduced half-life, and multiple violations of drug-likeness parameters, undermining its efficacy. Molecular dynamics simulations and Gibbs free energy assessments revealed that the four identified compounds maintain stable interactions with key residues in the FTO protein’s active site. We propose further validation through extensive In vitro, In vivo, and clinical studies to ascertain the therapeutic potential of these compounds in combating obesity.

Targeting acetylcholinesterase is one of the most important strategies for developing therapeutics against Alzheimer’s disease. In this work, we have employed a new approach that combines machine learning models, a multi-step similarity search of the PubChem library and molecular dynamics simulations to investigate potential inhibitors for acetylcholinesterase. Our search strategy has been shown to significantly enrich the set of compounds with strong predicted binding affinity to acetylcholinesterase. Both machine learning prediction and binding free energy calculation, based on linear interaction energy, suggest that the compound CID54414454 would bind strongly to acetylcholinesterase and hence is a promising inhibitor.

Abstract Background Cucurbitacins are present in some common vegetables as secondary metabolites and are used by the plants against harmful microbes. Exploration of this capability of natural product based substances against wide variety of microbes seems relevant due to the ease of availability of the resources and safety. In this regard, considering the current pandemic, the antiviral properties of these molecules with a subset of Cucurbitacin I structural derivatives have been screened. The inhibition potential of the phytochemicals was assessed by the stability of the protein–ligand complex formed with the nucleocapsid protein (PDB ID: 7CDZ) of SARS-CoV-2 by computational methods. The proposition of an alternate antiviral candidate that is cost-effective and efficient relative to existing formulations is the main objective of this work. Results Server-based molecular docking experiments revealed CBN19 (PubChem CID: 125125068) as a hit candidate among 101 test compounds, a reference molecule (K31), and 5 FDA-approved drugs in terms of binding affinities sorted out based on total energies. The molecular dynamics simulations (MDS) showed moderate stability of the protein-CBN19 complex as implied by various geometrical parameters RMSD, Rg, RMSF, SASA and hydrogen bond count. The ligand RMSD of 3.0 ± 0.5 Å, RMSF of Cα of protein with less than 5 Å, and smooth nature of SASA and Rg curves were calculated for the adduct. The binding free energy (− 47.19 ± 6.24 kcal/mol) extracted from the MDS trajectory using the MMGBSA method indicated spontaneity of the reaction between CBN19 and the protein. The multiple ADMET studies of the phytochemicals predicted some drug-like properties with minimal toxicity that mandate experimental verification. Conclusions Based on all the preliminary in silico results, Cucurbitacin, CBN19 could be proposed as a potential inhibitor of nucleocapsid protein theoretically capable of curing the disease. The proposed molecule is recommended for further in vitro and in vivo trials in the quest to develop effective and alternate therapeutics from plant-based resources against COVID-19.

T cell transmembrane, Immunoglobulin, and Mucin (TIM) are important immune system proteins which are especially present in T-cells and regulated the immune system by sensing cell engulfment and apoptotic processes. Their role is exerted by the capacity to detect the presence of phosphatidyl-serine lipid polar head in the outer leaflet of cellular membranes (correlated with apoptosis). In this contribution by using equilibrium and enhanced sampling molecular dynamics simulation we unravel the molecular bases and the thermodynamics of TIM, and in particular TIM-3, interaction with phosphatidyl serine in a lipid bilayer. Since TIM-3 deregulation is an important factor of prooncogenic tumor micro-environment understanding its functioning at a molecular level may pave the way to the development of original immunotherapeutic approaches. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Background: Cucurbitacins are present in some common vegetables as secondary metabolites and are used by the plants against harmful microbes. Exploration of this capability of natural product based substances against wide variety of microbes seems relevant due to the ease of availability of the resources and safety. In this regard, considering the current pandemic, the antiviral properties of these molecules with a subset of Cucurbitacin I structural derivatives have been screened. The inhibition potential of the phytochemicals was assessed by the stability of the protein–ligand complex formed with the nucleocapsid protein (PDB ID: 7CDZ) of SARS-CoV-2 by computational methods. The proposition of an alternate antiviral candidate that is cost-effective and efficient relative to existing formulations is the main objective of this work. Results: Server-based molecular docking experiments revealed CBN19 (PubChem CID: 125125068) as a hit candidate among 101 test compounds, a reference molecule (K31), and 5 FDA-approved drugs in terms of binding affinities sorted out based on total energies. The molecular dynamics simulations (MDS) showed moderate stability of the protein-CBN19 complex as implied by various geometrical parameters RMSD, Rg, RMSF, SASA and hydrogen bond count. The ligand RMSD of 3.0 ± 0.5 Å, RMSF of Cα of protein with less than 5 Å, and smooth nature of SASA and Rg curves were calculated for the adduct. The binding free energy (− 47.19 ± 6.24 kcal/mol) extracted from the MDS trajectory using the MMGBSA method indicated spontaneity of the reaction between CBN19 and the protein. The multiple ADMET studies of the phytochemicals predicted some drug-like properties with minimal toxicity that mandate experimental verification. Conclusions: Based on all the preliminary in silico results, Cucurbitacin, CBN19 could be proposed as a potential inhibitor of nucleocapsid protein theoretically capable of curing the disease. The proposed molecule is recommended for further in vitro and in vivo trials in the quest to develop effective and alternate therapeutics from plant-based resources against COVID-19. [ABSTRACT FROM AUTHOR]

The investigation employed cyclic voltammetry (CV) assays to assess the scavenging efficacy of two recently developed compounds, namely meso-tetramethophenyl-porphyrin TPPH2(o-methyl) and mesotetrabiphenyl-porphyrin (TbiPPH2), against the superoxide anion radical (O2-). The IC50 values derived from the CV assays indicated significant scavenging activity for both compounds, with TbPPH2 exhibiting superior potency (85.79 ± 0.11 μg ml-1) compared to the standard antioxidant alpha-tocopherol (353.27 ± 3.21 μg ml-1). Additionally, molecular docking simulations elucidated the interaction of the investigated compounds with specific amino acid residues of glutathione reductase through hydrogen bonding and hydrophobic interactions. The in vitro and in silico results were concordant, highlighting TbiPPH2 as the least active compound against glutathione reductase, boasting the highest inhibitory concentration of 0.63 μM and the lowest docking score of -35.36 kJ mol-1, thus positioning it as a promising candidate for antioxidant applications. [ABSTRACT FROM AUTHOR]

We utilized molecular dynamics (MD) simulations and Molecular Mechanics Poisson–Boltzmann Surface Area (MMPBSA) free energy calculations to investigate the specificity of two oligonucleotide probes, namely probe B and probe D, in detecting single-stranded DNA (ssDNA) within three bacteria families: Enterobacteriaceae, Pasteurellaceae, and Vibrionaceae. Due to the limited understanding of molecular mechanisms in the previous research, we have extended the discussion to focus specifically on investigating the binding process of bacteria-probe DNA duplexes, with an emphasis on analyzing the binding free energy. The role of electrostatic contributions in the specificity between the oligonucleotide probes and the bacterial ssDNAs was investigated and found to be crucial. Our calculations yielded results that were highly consistent with the experimental data. Through our study, we have successfully exhibited the benefits of utilizing in-silico approaches as a powerful virtual-screening tool, particularly in research areas that demand a thorough comprehension of molecular interactions. [ABSTRACT FROM AUTHOR]

Mitotic kinesins are eukaryotic proteins that play a vital role in cellular mitosis. Their over-expression in malignant rather than normal cells and their specific cellular role made kinesin inhibitors a promising cancer therapeutics. The realization of in-vitro antitumor activity of the investigational molecule-monastrol-was traced to its allosteric inhibition of the ATPase activity of the motor domain of Human Kensin-5 (Eg5) and prompted extensive efforts towards kinesin inhibitors. Many reports pointed to the prospect of Kinesin-like protein (KIFC1) as a novel anticancer target. Nevertheless, no verified KIFC1-inhibitor crystallized structure has been reported so far, confirming the scarcity of molecular studies devoted to deciphering claimed potentiality. The significant structural resemblance across the kinesins superfamily sparked our interest in investigating monastrol as a KIFC1 inhibitor.Time-scale findings of molecular dynamics simulation and molecular mechanics/generalized-born surface area (MM/GBSA) methods revealed that monastrol binds with high affinity to an allosteric pocket, inducing notable dynamical alterations evidenced by increased structural stability, rigidity, compactness, and overall folding tendency of KIFC1. Further, these conformational events negatively impacted the affinity of ATP to its site disrupting the essential ATP-KIFC1 dynamics leading to consequential loss of functionality. We concluded that monastrol can act as non-competitive inhibitor of KIFC1 and these findings speculate new anticancer mechanism contributing to the design of highly selective and novel cancer therapeutics.

Serine hydroxymethyltransferase 2 (SHMT2) has garnered significant attention as a critical catalytic regulator of the serine/glycine pathway in the one-carbon metabolism of cancer cells. Despite its potential as an anti-cancer target, only a limited number of inhibitors have been identified so far. In this study, we employed seven different scoring functions and skeleton clustering to screen the ChemDiv database for 38 compounds, 20 of which originate from the same skeleton structure. The most significant residues from SHMT2 and chemical groups from the inhibitors were identified using ASGBIE (Alanine Scanning with Generalized Born model and Interaction Entropy), and the binding energy of each residue was quantitatively determined, revealing the essential features of the protein–inhibitor interaction. The two most important contributing residues are TYR105 and TYR106 of the B chain followed by LEU166 and ARG425 of the A chain. The findings will be greatly helpful in developing a thorough comprehension of the binding mechanisms involved in drug–SHMT2 interactions and offer valuable direction for designing more potent inhibitors.

The major histocompatibility complex (MHC) can recognize and bind to external peptides to generate effective immune responses by presenting the peptides to T cells. Therefore, understanding the binding modes of peptide–MHC complexes (pMHC) and predicting the binding affinity of pMHCs play a crucial role in the rational design of peptide vaccines. In this study, we employed molecular dynamics (MD) simulations and free energy calculations with an Alanine Scanning with Generalized Born and Interaction Entropy (ASGBIE) method to investigate the protein–peptide interaction between HLA-A*02:01 and the G9209 peptide derived from the melanoma antigen gp100. The energy contribution of individual residue was calculated using alanine scanning, and hotspots on both the MHC and the peptides were identified. Our study shows that the pMHC binding is dominated by the van der Waals interactions. Furthermore, we optimized the ASGBIE method, achieving a Pearson correlation coefficient of 0.91 between predicted and experimental binding affinity for mutated antigens. This represents a significant improvement over the conventional MM/GBSA method, which yields a Pearson correlation coefficient of 0.22. The computational protocol developed in this study can be applied to the computational screening of antigens for the MHC1 as well as other protein–peptide binding systems. [ABSTRACT FROM AUTHOR]

Density functional theory (DFT) calculations and molecular docking have been carried out on natural products containing eugenol, gingerol, ascorbic acid, oleurpoein, piperine, hesperidin, quercetin, Luteolin, and curcumin in order to predict their biological activities and to analyze their pancreatic lipase inhibition. The biological activity predictions are based on the global and local chemical descriptors, namely, HOMO–LUMO gaps, chemical hardness, chemical potential, electrophilicity, dipole moment, and Fukui functions. Our findings show that the studied compounds can be divided into two groups based on the chemical descriptors; the first group is composed of eugenol, gingerol, ascorbic acid, and oleuropein and the second one is composed of piperine, hesperidin, quercetin, Luteolin, and curcumin depending on the HOMO–LUMO gaps and electrophilicity values predicting best reactivity for the second group than the first one. The frontier orbitals offer a deeper insight concerning the electron donor and electron acceptor capabilities, whereas the local descriptors resulting from Fukui functions put emphasis on the active sites of different candidate ligands. The molecular docking was performed in order to compare and identify the inhibition activity of the natural candidate ligands against pancreatic lipase which were compared to that of synthesized ones. The molecular docking results revealed that the Luteolin compound has the best binding affinity of −8.56 kcal/mol due to their unique molecular structure and the position of -OH aromatic substituents. [ABSTRACT FROM AUTHOR]

Indoleamine 2,3-dioxygenase-1 (IDO-1) is a heme-containing enzyme that initiates the kynurenine pathway by catalyzing the first step in l-tryptophan catabolism. IDO-1 has been shown to play an important role in immunosuppressive mechanisms and tumor evasion, making it an attractive target for therapeutic intervention, a computer-aided drug design (CADD) approach was applied to a set of 34 of 4,5-Disubstituted 1,2,3-triazole derivatives that had been evaluated for their IC50 values against indoleamine 2,3-dioxygenase 1 (IDO1) enzyme. By employing atom-based 3-QSAR pharmacophores and field-based 3D-QSARs, the study identified specific chemical groups and structural locations that could be modified to enhance the compounds' activity against IDO1 in order to discover more effective inhibitors. The study utilized atom-based 3-QSAR pharmacophores and field-based 3D-QSARs to model the 4,5-Disubstituted 1,2,3-triazole derivatives against IDO1, leading to the identification of specific chemical groups and structural regions that could be altered to enhance the compounds' activity. The triazole derivatives were subjected to molecular docking, yielding docking scores of − 7.12 kcal/mol for compound 25, and − 7.1, − 7.4, − 7.4, − 8.1, and − 8.3 kcal/mol for the five newly designed molecules T01-T05, respectively. Moreover, an assessment of the free energy was conducted to determine the energetic factors that contribute to the stability of the compounds within the enzyme's binding site. [ABSTRACT FROM AUTHOR]

Amid the ongoing monkeypox outbreak, there is an urgent need for the rapid development of effective therapeutic interventions capable of countering the immune evasion mechanisms employed by the monkeypox virus (MPXV). The evasion strategy involves the binding of the F3L protein to dsRNA, resulting in diminished interferon (IFN) production. Consequently, our current research focuses on utilizing virtual drug screening techniques to target the RNA binding domain of the F3L protein. Out of the 954 compounds within the South African natural compound database, only four demonstrated notable docking scores: −6.55, −6.47, −6.37, and −6.35 kcal/mol. The dissociation constant (KD) analysis revealed a stronger binding affinity of the top hits 1-4 (−5.34, −5.32, −5.29, and −5.36 kcal/mol) with the F3L in the MPXV. All-atom simulations of the top-ranked hits 1 to 4 consistently exhibited stable dynamics, suggesting their potential to interact effectively with interface residues. This was further substantiated through analyses of parameters such as radius of gyration (Rg), Root Mean Square Fluctuation, and hydrogen bonding. Cumulative assessments of binding free energy confirmed the top-performing candidates among all the compounds, with values of −35.90, −52.74, −28.17, and −32.11 kcal/ mol for top hits 1-4, respectively. These results indicate that compounds top hit 1- 4 could hold significant promise for advancing innovative drug therapies, suggesting their suitability for both in vivo and in vitro experiments. [ABSTRACT FROM AUTHOR]

Angiogenesis blockade represents a therapeutic strategy to inhibit the growth of the tumour and its progression and metastasis. Targeting the vascular endothelial growth factor receptor 2 (VEGFR2) is among the approaches approved as anti-cancer drugs. In this study, we examined ARA-linker-TGFaL3 and TGFaL3 binding affinity to VEGFR2. Next, the cytotoxicity effect of ARA-linker-TGFaL3 on human umbilical vein endothelial cells was evaluated. The 100 ns molecular dynamic simulation was employed to estimate the stability of the ligand-receptor interaction and the free energy decomposition was performed by molecular mechanics generalised Born surface area method. The MTT test evaluated the proliferation inhibition of ARA-linker-TGFaL3 and arazyme on HUVECs cells. Also, the change in VEGFR2 gene expression was investigated after treatment with recombinant proteins. Analysis of the trajectory using the root-mean-square deviation and fluctuation, radius of gyration, H-bond calculation, and binding free energy showed that ARA-linker-TGFaL3 formed the more stable complex with the D2 and D3 domains of VEGFR2 than TGFaL3. Meanwhile, ARA-linker-TGFaL3 revealed higher cytotoxicity and inhibition of VEGFR2 expression than arazyme. The results of the current study suggest the anti-angiogenesis effects of ARA-linker-TGFaL3 that can be useful in cancer therapy. [ABSTRACT FROM AUTHOR]

The accurate prediction of binding free energy is a major challenge in structure-based drug design. Quantum mechanics (QM)-based approaches show promising potential in predicting ligand–protein binding affinity by accurately describing the behavior and structure of electrons. However, traditional QM calculations face computational limitations, hindering their practical application in drug design. Nevertheless, the fragment molecular orbital (FMO) method has gained widespread application in drug design due to its ability to reduce computational costs and achieve efficient ab initio QM calculations. Although the FMO method has demonstrated its reliability in calculating the gas phase potential energy, the binding of proteins and ligands also involves other contributing energy terms, such as solvent effects, the 'deformation energy' of a ligand's bioactive conformations, and entropy. Particularly in cases involving ionized fragments, the calculation of solvation free energy becomes particularly crucial. We conducted an evaluation of some previously reported implicit solvent methods on the same data set to assess their potential for improving the performance of the FMO method. Herein, we develop a new QM-based binding free energy calculation method called FMOScore, which enhances the performance of the FMO method. The FMOScore method incorporates linear fitting of various terms, including gas-phase potential energy, deformation energy, and solvation free energy. Compared to other widely used traditional prediction methods such as FEP+, MM/PBSA, MM/GBSA, and Autodock vina, FMOScore showed good performance in prediction accuracies. By constructing a retrospective case study, it was observed that incorporating calculations for solvation free energy and deformation energy can further enhance the precision of FMO predictions for binding affinity. Furthermore, using FMOScore-guided lead optimization against Src homology-2-containing protein tyrosine phosphatase 2 (SHP-2), we discovered a novel and potent allosteric SHP-2 inhibitor (compound 8). [ABSTRACT FROM AUTHOR]

The kinesin spindle protein (Eg5) is a mitotic protein that plays an essential role in the formation of the bipolar spindles during the mitotic phase. Eg5 protein controls the segregation of the chromosomes in mitosis which renders it a vital target for cancer treatment. In this study our approach to identifying novel scaffold for Eg5 inhibitors is based on targeting the novel allosteric pocket (α4/α6/L11). Extensive computational techniques were applied using ligand-based virtual screening and molecular docking by two approaches, MOE and AutoDock, to screen a library of commercial compounds. We identified compound 8-(3-(1H-imidazol-1-ylpropylamino)-3-methyl-7-((naphthalen-3-yl)methyl)-1H-purine-2, 6 (3H,7H)-dione (compound 5) as a novel scaffold for Eg5 inhibitors. This compound inhibited cancer cell Eg5 ATPase at 2.37 ± 0.15 µM. The molecular dynamics simulations revealed that the identified compound formed stable interactions in the allosteric pocket (α4/α6/L11) of the receptor, indicating its potential as a novel Eg5 inhibitor. [ABSTRACT FROM AUTHOR]

Serine hydroxymethyltransferase 2 (SHMT2) has garnered significant attention as a critical catalytic regulator of the serine/glycine pathway in the one-carbon metabolism of cancer cells. Despite its potential as an anti-cancer target, only a limited number of inhibitors have been identified so far. In this study, we employed seven different scoring functions and skeleton clustering to screen the ChemDiv database for 38 compounds, 20 of which originate from the same skeleton structure. The most significant residues from SHMT2 and chemical groups from the inhibitors were identified using ASGBIE (Alanine Scanning with Generalized Born model and Interaction Entropy), and the binding energy of each residue was quantitatively determined, revealing the essential features of the protein–inhibitor interaction. The two most important contributing residues are TYR105 and TYR106 of the B chain followed by LEU166 and ARG425 of the A chain. The findings will be greatly helpful in developing a thorough comprehension of the binding mechanisms involved in drug–SHMT2 interactions and offer valuable direction for designing more potent inhibitors. [ABSTRACT FROM AUTHOR]

The investigation employed cyclic voltammetry (CV) assays to assess the scavenging efficacy of two recently developed compounds, namely meso-tetramethophenyl-porphyrin TPPH2(o-methyl) and meso-tetrabiphenyl-porphyrin (TbiPPH2), against the superoxide anion radical ( ). The IC50 values derived from the CV assays indicated significant scavenging activity for both compounds, with TbPPH2 exhibiting superior potency (85.79 ± 0.11 µg ml-1) compared to the standard antioxidant alpha-tocopherol (353.27 ± 3.21 µg ml-1). Additionally, molecular docking simulations elucidated the interaction of the investigated compounds with specific amino acid residues of glutathione reductase through hydrogen bonding and hydrophobic interactions. The in vitro and in silico results were concordant, highlighting TbiPPH2 as the least active compound against glutathione reductase, boasting the highest inhibitory concentration of 0.63 μM and the lowest docking score of -35.36 kJ mol-1, thus positioning it as a promising candidate for antioxidant applications.

Despite the global implementation of prequalified oral vaccines by the World Health Organization (WHO) in numerous countries, rotavirus A (RVA) have continued to be the principal cause of acute dehydrating diarrhoea in children under five years of age. Unfortunately, there are no authorized anti-rotaviral medications. Hence, it is crucial to prioritize the development of specialized therapeutics to combat rotaviral infections. For the first time, Spondias mombin, Macaranga barteri and Dicerocaryum eriocarpum metabolites were screened using computational techniques to identify potential novel modulators with broad-spectrum activity against VP7 epitopes (capsid protein) of RVA. Compounds with poor pharmacokinetics and drug-likeness were screened out from the initial top 20 metabolites identified using molecular docking. Thereafter, molecular dynamics (MD) simulation was used to assess the ability of the resulting compounds to modulate the selected VP7 epitopes. Remarkably, all the lead compounds had higher negative binding free energy than tizoxanide across the three epitopes of VP7, with apigenin-4′-glucoside having the highest affinity for VP7A (−24.13 kcal/mol) and VP7C (−43.67 kcal/mol) while the highest affinity for VP7D was observed in 2SG (−36.08 kcal/mol). Interestingly, 2SG (−18.24 kcal/mol, −31.21 kcal/mol, −36.08 kcal/mol), apigenin-4′-glucoside (−24.13 kcal/mol, −43.67 kcal/mol, −33.52 kcal/mol) and gnetin L (−21.21 kcal/mol, −27.56 kcal/mol, −32.48 kcal/mol) had better broad-spectrum affinities for VP7A, C and D relative to tizoxanide (−10.36 kcal/mol, −18.32 kcal/mol, −12.98 kcal/mol) respectively. Generally, the compounds are thermodynamically stable with 2SG (1.88 Å), ellagic acid (2.45 Å) and sericetin (2.22 Å) being the most stable against VP7A, C and D respectively. While this study unearths the lead compounds' promising ability to modulate the investigated VP7 epitopes, further confirmatory in vitro and in vivo studies are imperative, and efforts are underway towards achieving this task.

Mycobacterium tuberculosis (Mtb) is responsible for the spread of tuberculosis (TB). The current study employed virtual screening of 2569 natural compounds against the DNA-directed RNA polymerase (RNAP) of Mtb to identify the possible binders that can inhibit its function. The in-silico methodology included molecular docking to the compounds, further, the stability and flexibility of the best complexes were studied using molecular dynamics simulation, the MM/GBSA binding free energy technique with energy decomposition, PCA, FEL, steered MD simulation, and umbrella sampling. Individual virtual screenings were conducted for the five RNAP subunits (chains A, B, C, D, and E) to identify a compound capable of inhibiting RNAP oligomerization. A promising compound, isoestradiol 3-benzoate, exhibited a low binding score (−7.28 ​kcal/mol to −8.21 ​kcal/mol) and showed binding ability with all subunits of the protein. Thus, the five complexes with isoestradiol 3-benzoate were selected for molecular dynamics simulation analysis. Furthermore, RMSD showed that isoestradiol 3-benzoate bound with chain E showed the lowest RMSD of 0.49 ​nm, while with chains A and B it had the most stable and consistent conformations with RMSD of 1.75 ​nm and 1.2 ​nm, respectively. The H-bond between isoestradiol 3-benzoate and chains C and E showed the highest occupancy (58.27 ​%, 45.33 ​%, and 50.80 ​%, 42.25 ​%, 11.75 ​%). Moreover, the MMPBSA technique showed that isoestradiol 3-benzoate had a strong association with chains B and C (ΔGbind ​= ​−126.25 ​± ​2.03 and −129.27 ​± ​2.25). Additionally, free energy decomposition, PCA, FEL-steered MD simulation, and umbrella sampling were also performed to validate the association of the ligand with the protein. Isoestradiol 3-benzoate binds strongly to chains B and E; therefore, it should be considered as viable candidate for inhibiting the formation of RNAP protein complex, concluded in this study.

Introduction: Ciprofloxacin antibiotic is used in the treatment of retinal toxicity or retinopathy. The present study aimed to assess the effect of ciprofloxacin on rhodopsin protein structure and the stability or instability of this protein in the presence of this medicine. The type of drug and protein binding is effective in the elimination or interaction of the medicine with the target tissues. Material & Methods: Thermodynamic components can be obtained in the interactions between rhodopsin protein and ciprofloxacin using docking software. Docking studies were performed by AutoDock 4.2 software. Pymol, Ligplot, and VMD graphic software packeages were used to observe the docking performed. Findings: Based on the results obtained from docking studies, the most important bond involved in the binding of ciprofloxacin drug with rhodopsin protein is hydrophobic bonds and hydrogen bonds. The estimate of Gibbs free energies (kcal/mol) for the best docking model is equal to -6.5. This model with the lowest level of binding energy has the greatest tendency to bind to rhodopsin amino acids, and negative values of ΔG° are indicative of a spontaneous process. Discussion & Conclusion: Based on the docking results, the A position of the rhodopsin protein is a suitable place for ciprofloxacin to bind to this protein, and the complex of ciprofloxacin with the rhodopsin protein can cause rhodopsin to regenerate so that it can start the process of seeing normally. In fact, the strong hydrogen bond between the nitrogen atom in the ciprofloxacin structure and the amino acid arginine plays a key role in stabilizing the complex.

Bromodomain-containing protein 9 (BRD9) is a key player in chromatin remodeling and gene expression regulation, and it is closely associated with the development of various diseases, including cancers. Recent studies have indicated that inhibition of BRD9 may have potential value in the treatment of certain cancers. Molecular dynamics (MD) simulations, Markov modeling and principal component analysis were performed to investigate the binding mechanisms of allosteric inhibitor POJ and orthosteric inhibitor 82I to BRD9 and its allosteric regulation. Our results indicate that binding of these two types of inhibitors induces significant structural changes in the protein, particularly in the formation and dissolution of α-helical regions. Markov flux analysis reveals notable changes occurring in the α-helicity near the ZA loop during the inhibitor binding process. Calculations of binding free energies reveal that the cooperation of orthosteric and allosteric inhibitors affects binding ability of inhibitors to BRD9 and modifies the active sites of orthosteric and allosteric positions. This research is expected to provide new insights into the inhibitory mechanism of 82I and POJ on BRD9 and offers a theoretical foundation for development of cancer treatment strategies targeting BRD9.

Inhibiting MDM2-p53 interaction is considered an efficient mode of cancer treatment. In our current study, Gaussian-accelerated molecular dynamics (GaMD), deep learning (DL), and binding free energy calculations were combined together to probe the binding mechanism of non-peptide inhibitors K23 and 0Y7 and peptide ones PDI6W and PDI to MDM2. The GaMD trajectory-based DL approach successfully identified significant functional domains, predominantly located at the helixes α2 and α2’, as well as the β-strands and loops between α2 and α2’. The post-processing analysis of the GaMD simulations indicated that inhibitor binding highly influences the structural flexibility and collective motions of MDM2. Calculations of molecular mechanics–generalized Born surface area (MM-GBSA) and solvated interaction energy (SIE) not only suggest that the ranking of the calculated binding free energies is in agreement with that of the experimental results, but also verify that van der Walls interactions are the primary forces responsible for inhibitor–MDM2 binding. Our findings also indicate that peptide inhibitors yield more interaction contacts with MDM2 compared to non-peptide inhibitors. Principal component analysis (PCA) and free energy landscape (FEL) analysis indicated that the piperidinone inhibitor 0Y7 shows the most pronounced impact on the free energy profiles of MDM2, with the piperidinone inhibitor demonstrating higher fluctuation amplitudes along primary eigenvectors. The hot spots of MDM2 revealed by residue-based free energy estimation provide target sites for drug design toward MDM2. This study is expected to provide useful theoretical aid for the development of selective inhibitors of MDM2 family members.

Amid the ongoing monkeypox outbreak, there is an urgent need for the rapid development of effective therapeutic interventions capable of countering the immune evasion mechanisms employed by the monkeypox virus (MPXV). The evasion strategy involves the binding of the F3L protein to dsRNA, resulting in diminished interferon (IFN) production. Consequently, our current research focuses on utilizing virtual drug screening techniques to target the RNA binding domain of the F3L protein. Out of the 954 compounds within the South African natural compound database, only four demonstrated notable docking scores: −6.55, −6.47, −6.37, and −6.35 kcal/mol. The dissociation constant (KD) analysis revealed a stronger binding affinity of the top hits 1-4 (−5.34, −5.32, −5.29, and −5.36 kcal/mol) with the F3L in the MPXV. All-atom simulations of the top-ranked hits 1 to 4 consistently exhibited stable dynamics, suggesting their potential to interact effectively with interface residues. This was further substantiated through analyses of parameters such as radius of gyration (Rg), Root Mean Square Fluctuation, and hydrogen bonding. Cumulative assessments of binding free energy confirmed the top-performing candidates among all the compounds, with values of −35.90, −52.74, −28.17, and −32.11 kcal/mol for top hits 1-4, respectively. These results indicate that compounds top hit 1-4 could hold significant promise for advancing innovative drug therapies, suggesting their suitability for both in vivo and in vitro experiments.

N-ferrocenylmethylaniline (FA) and its N-acetylated derivative (NFA) have been synthesized and fully characterized by various physicochemical techniques such as 1H and 13C NMR spectroscopy, their interactions with chicken blood DNA (CB-DNA) were studied by cyclic voltammetry (CV) and molecular docking (MD). The obtained results suggested that both FA and NFA bind strongly via electrostatic interactions to the minor groove of double helix DNA, these electrostatic interactions were evidenced by the findings like a negative formal potential shift in CV and ionic strength effect. The results further show that the obtained binding constants and free binding energies by MD analysis are matched roughly to those obtained from CV. Furthermore, the binding site size was evaluated from voltametric data.

Papain-like protease (PLpro), a non-structural protein encoded by SARS-CoV-2, is an important therapeutic target. Regions 1 and 5 of an existing drug, GRL0617, can be optimized to produce cooperativity with PLpro binding, resulting in stronger binding affinity. This work investigated the origin of the cooperativity using molecular dynamics simulations combined with the interaction entropy (IE) method. The regions' improvement exhibits cooperativity by calculating the binding free energies between the complex of PLpro-inhibitor. The thermodynamic integration method further verified the cooperativity generated in the drug improvement. To further determine the specific source of cooperativity, enthalpy and entropy in the complexes were calculated using molecular mechanics/generalized Born surface area and IE. The results show that the entropic change is an important contributor to the cooperativity. Our study also identified residues P248, Q269, and T301 that play a significant role in cooperativity. The optimization of the inhibitor stabilizes these residues and minimizes the entropic loss, and the cooperativity observed in the binding free energy can be attributed to the change in the entropic contribution of these residues. Based on our research, the application of cooperativity can facilitate drug optimization, and provide theoretical ideas for drug development that leverage cooperativity by reducing the contribution of entropy through multi-locus binding. [ABSTRACT FROM AUTHOR]

[Display omitted] Based both on the practice of post-processing by a human expert and on the higher values of the accuracy metrics of machine learning scoring functions, it is suggested that when estimating the free energy of binding in a ligand–receptor complex, a significant part of intermolecular interactions is still not explicitly taken into account. An assessment is made of how explicit consideration of non-complementary ligand–receptor interactions could improve the accuracy of the description of contemporary classical scoring functions, which tend to use only terms of complementary/favorable interactions. [ABSTRACT FROM AUTHOR]

[Display omitted] Clathrate hydrates form and grow at interfaces. Understanding the relevant molecular processes is crucial for developing hydrate-based technologies. Many computational studies focus on hydrate growth within the aqueous phase using the 'direct coexistence method', which is limited in its ability to investigate hydrate film growth at hydrocarbon-water interfaces. To overcome this shortcoming, a new simulation setup is presented here, which allows us to study the growth of a methane hydrate nucleus in a system where oil–water, hydrate-water, and hydrate-oil interfaces are all simultaneously present, thereby mimicking experimental setups. Using this setup, hydrate growth is studied here under the influence of two additives, a polyvinylcaprolactam oligomer and sodium dodecyl sulfate, at varying concentrations. Our results confirm that hydrate films grow along the oil–water interface, in general agreement with visual experimental observations; growth, albeit slower, also occurs at the hydrate-water interface, the interface most often interrogated via simulations. The results obtained demonstrate that the additives present within curved interfaces control the solubility of methane in the aqueous phase, which correlates with hydrate growth rate. Building on our simulation insights, we suggest that by combining data for the potential of mean force profile for methane transport across the oil–water interface and for the average free energy required to perturb a flat interface, it is possible to predict the performance of additives used to control hydrate growth. These insights could be helpful to achieve optimal methane storage in hydrates, one of many applications which are attracting significant fundamental and applied interests. [ABSTRACT FROM AUTHOR]

CYP 3A4 and CYP 3A5 are two important members of the human cytochrome P450 family. Although their overall structures are similar, the local structures of the active site are different, which directly leads to obvious individual differences in drug metabolic efficacy and toxicity. In this work, midazolam (MDZ) was selected as the probe substrate, and its interaction with two proteins, CYP 3A4 and CYP 3A5, was studied by molecular dynamics simulation (MD) along with the calculation of the binding free energy. The results show that two protein–substrate complexes have some similarities in enzyme–substrate binding; that is, in both complexes, Ser119 forms a high occupancy hydrogen bond with MDZ, which plays a key role in the stability of the interaction between MDZ and the enzymes. However, the complex formed by CYP 3A4 and MDZ is more stable, which may be attributed to the sandwich structure formed by the fluorophenyl group of the substrate with Leu216 and Leu482. Our study interprets the binding differences between two isoform–substrate complexes and reveals a structure–function relationship from the atomic perspective, which is expected to provide a theoretical basis for accurately measuring the effectiveness and toxicity of drugs for individuals in the era of precision medicine. [ABSTRACT FROM AUTHOR]

SARS‐CoV‐2 gained crucial mutations at the receptor binding domain (RBD) that often changed the course of the pandemic leading to new waves with increased case fatality. Variants are observed with enhanced transmission and immune invasion abilities. Thus, predicting future variants with enhanced transmission ability is a problem of utmost research interest. Here, we have developed a multi‐tier exhaustive SARS‐CoV‐2 mutation screening platform combining MM/GBSA, extensive molecular dynamics simulations, and steered molecular dynamics to identify RBD mutants with enhanced ACE2 binding capability. We have identified four RBM mutations (F490K, S494K, G504F, and the P499L) with significantly higher ACE2 binding abilities than wild‐type RBD. Compared to wild‐type RBD, they all form stable complexes with more hydrogen bonds and salt‐bridge interactions with ACE2. Our simulation data suggest that these mutations allosterically alter the packing of the RBM interface of the RBD‐ACE2 complex. As a result, the rupture force required to break the RBD‐ACE2 contacts is significantly higher for these mutants. [ABSTRACT FROM AUTHOR]

Introduction: Hypoxia-inducible factor (HIF) prolyl hydroxylase domain (PHD) enzymes are major therapeutic targets of anemia and ischemic/hypoxia diseases. To overcome safety issues, liver failure, and problems associated with on-/off-targets, natural products due to their novel and unique structures offer promising alternatives as drug targets. Methods: In the current study, the Marine Natural Products, North African, South African, East African, and North-East African chemical space was explored for HIF-PHD inhibitors discovery through molecular search, and the final hits were validated using molecular simulation and free energy calculation approaches. Results: Our results revealed that CMNPD13808 with a docking score of -8.690 kcal/mol, CID15081178 with a docking score of -8.027 kcal/mol, CID71496944 with a docking score of -8.48 kcal/mol and CID11821407 with a docking score of -7.78 kcal/mol possess stronger activity than the control N-[(4-hydroxy-8-iodoisoquinolin-3-yl)carbonyl]glycine, 4HG (-6.87 kcal/mol). Interaction analysis revealed that the target compounds interact with Gln239, Tyr310, Tyr329, Arg383 and Trp389 residues, and chelate the active site iron in a bidentate manner in PHD2. Molecular simulation revealed that these target hits robustly block the PHD2 active site by demonstrating stable dynamics. Furthermore, the half-life of the Arg383 hydrogen bond with the target ligands, which is an important factor for PHD2 inhibition, remained almost constant in all the complexes during the simulation. Finally, the total binding free energy of each complex was calculated as CMNPD13808-PHD2-72.91 kcal/mol, CID15081178-PHD2-65.55 kcal/mol, CID71496944-PHD2-68.47 kcal/mol, and CID11821407-PHD2-62.06 kcal/mol, respectively. Conclusion: The results show the compounds possess good activity in contrast to the control drug (4HG) and need further in vitro and in vivo validation for possible usage as potential drugs against HIF-PHD2-associated diseases. [ABSTRACT FROM AUTHOR]

In the current study, we used molecular screening and simulation approaches to target I7L protease from monkeypox virus (mpox) from the Traditional Chinese Medicines (TCM) database. Using molecular screening, only four hits TCM27763, TCM33057, TCM34450 and TCM31564 demonstrated better pharmacological potential than TTP6171 (control). Binding of these molecules targeted Trp168, Asn171, Arg196, Cys237, Ser240, Trp242, Glu325, Ser326, and Cys328 residues and may affect the function of I7L protease in in vitro assay. Moreover, molecular simulation revealed stable dynamics, tighter structural packing and less flexible behaviour for all the complexes. We further reported that the average hydrogen bonds in TCM27763, TCM33057, TCM34450 and TCM31564I7L complexes remained higher than the control drug. Finally, the BF energy results revealed −62.60 ± 0.65 for the controlI7L complex, for the TCM27763I7L complex −71.92 ± 0.70 kcal/mol, for the TCM33057I7L complex the BF energy was −70.94 ± 0.70 kcal/mol, for the TCM34450I7L the BF energy was −69.94 ± 0.85 kcal/mol while for the TCM31564I7L complex the BF energy was calculated to be −69.16 ± 0.80 kcal/mol. Although, we used stateoftheart computational methods, these are theoretical insights that need further experimental validation. [ABSTRACT FROM AUTHOR]

The entry of SARS-CoV-2 into the host cell is mediated by its S-glycoprotein (SGP). Sulfated glycans bind to the SGP receptor-binding domain (RBD), which forms a ternary complex with its receptor angiotensin converting enzyme 2. Here, we have conducted a thorough and systematic computational study of the binding of four oligosaccharide building blocks from novel marine sulfated glycans (isolated from Pentacta pygmaea and Isostichopus badionotus) to the non-glycosylated and glycosylated RBD. Blind docking studies using three docking programs identified five potential cryptic binding sites. Extensive site-targeted docking and molecular dynamics simulations using two force fields confirmed only two binding sites (Sites 1 and 5) for these novel, highly charged sulfated glycans, which were also confirmed by previously published reports. This work showed the structural features and key interactions driving ligand binding. A previous study predicted Site 2 to be a potential binding site, which was not observed here. The use of several molecular modeling approaches gave a comprehensive assessment. The detailed comparative study utilizing multiple modeling approaches is the first of its kind for novel glycan–SGP interaction characterization. This study provided insights into the key structural features of these novel glycans as they are considered for development as potential therapeutics. [ABSTRACT FROM AUTHOR]

New Delhi Metallo-β-lactamase (NDM-1) is an enzyme that hydrolyses a wide range of β-lactam antibiotics, including most carbapenems, leading to antimicrobial resistance. The development of a novel NDM-1 inhibitor for use in combination with carbapenems may help to combat drug-resistant pathogens. Twenty compounds were designed based on the structural features of the NDM-1 active site to inhibit bacterial NDM-1 and protect β-lactam antibiotics from enzyme attack. The designed molecules were naphthalene, thiazole, and sulfone derivatives because they could coordinate with the zinc ions and form hydrophobic contracts with the enzyme's active site. A molecular docking protocol was used to identify potential inhibitor(s) of the NDM-1 target protein. Furthermore, drug-likeness and pharmacokinetic properties of the designed molecules were predicted. Three compounds with the more negative ΔGbinding results were selected for further investigation using molecular dynamic (MD) simulations. T016 had a significantly more negative binding free energy than the positive control and other designed molecules, had stable MD simulations (Root-mean-square deviation < 0.5 Å), passed Lipinski's rule of five, and had favourable physicochemical and pharmacokinetic properties. The findings can be used to inform the synthesis and in vitro testing of the selected molecules. [ABSTRACT FROM AUTHOR]