Performed MD Simulations Research Articles

Unveiling the Potential of Bergenia Phenolics: Vitexin's Role in Allosteric Modulation of PBP2a as a Strategy against MRSA Resistance.

For cell wall biosynthesis, drug-resistant S. aureus uses a special protein called PBP2a, even when antibiotics are present and stop its natural processes from working. To combat this, novel therapies are required to specifically target PBP2a with greater efficacy. Using computational approaches, we screened nine phenolic compounds from other Bergenia species, including Bergenia ciliata, Begenia ligulata, Bergenia purpurascens, and Bergenia stracheyi, against the PBP2a allosteric site to explore the potential interaction between phenolic compounds and a specific region of PBP2a known as the allosteric site. Based on interaction patterns and estimated affinity, vitexin has been found to be the most prominent phenolic compound. We performed MD simulations on vitexin and ceftazidime as control molecules based on the docking results. The binding free energy estimates of vitexin (-94.48 +/- 17.92 kJ/mol) using MM/PBSA were lower than those of the control (-67.61 +/- 12.29 kJ/mol), which suggests that vitexin may be able to inhibit PBP2a activity in MRSA. It has been intriguing to observe a correlation between the affinity of the lead vitexin at the allosteric site and the modification of Tyr446, the active site gatekeeper residue in PBP2a. Our findings have implied that lead vitexin can either directly or indirectly decrease PBP2a activity by inducing allosteric site change in conventional medicine.

The Inferential Binding Sites of GCGR for Small Molecules Using Protein Dynamic Conformations and Crystal Structures.

Glucagon receptor (GCGR) is a class B1 G-protein-coupled receptor that plays a crucial role in maintaining human blood glucose homeostasis and is a significant target for the treatment of type 2 diabetes mellitus (T2DM). Currently, six small molecules (Bay 27-9955, MK-0893, MK-3577, LY2409021, PF-06291874, and LGD-6972) have been tested or are undergoing clinical trials, but only the binding site of MK-0893 has been resolved. To predict binding sites for other small molecules, we utilized both the crystal structure of the GCGR and MK-0893 complex and dynamic conformations. We docked five small molecules and selected the best conformation based on binding mode, docking score, and binding free energy. We performed MD simulations to verify the binding mode of the selected small molecules. Moreover, when selecting conformations, results of competitive binding were referred to. MD simulation indicated that Bay 27-9955 exhibits moderate binding stability in Pocket 3. MK-3577, LY2409021, and PF-06291874 exhibited highly stable binding to Pocket 2, consistent with experimental results. However, LY2409021 may also bind to Pocket 5. Additionally, LGD-6972 exhibited relatively stable binding in Pocket 5. We also conducted structural modifications of LGD-6972 based on the results of MD simulations and predicted its analogues' bioavailability, providing a reference for the study of GCGR small molecules.

Exploring the underlying mechanism of interaction of Sulindac with Human hemoglobin and Lysozyme: Multi-spectroscopic, molecular docking, DFT and MD simulation approaches

Contrasting behavior of Nonsteroidal anti-inflammatory drug Sulindac (SDC) towards two different proteins Human hemoglobin (HHb) and Lysozyme (LYS) has been explored by multispectroscopy, molecular docking, DFT and MD Simulation approaches. The fluorescence quenching experiments showed that SDC strongly binds with both proteins in a static manner. Alteration in the secondary structure of HHb and LYS in presence of SDC was further investigated by CD and UV–visible spectroscopy. It is observed that on addition of SDC, the % α-helix of native HHb decreases whereas it increases for LYS-SDC system substantiated the fact SDC stabilized the secondary structure of LYS and destabilized the HHb structure thus, showing the contrasting traits. Experimental results further validated by computational techniques. Molecular docking and DFT were conducted to study the binding sites, nature of interactions and HOMO-LUMO energy gap in both the systems which revealed that the binding of SDC with both proteins resulted in the considerable change in the molecular structure of the former. Additionally, we performed MD simulations to study the structural stability of Lysozyme and Hemoglobin, both unbound and bound to the Sulindac molecule. Sulindac binding showed distinct impacts on protein stability in both proteins, supported by global and essential dynamics.This study not only provides important insights into the binding of SDC with HHb and LYS but also it provides a useful direction in the pharmacology and clinical medicine fields.

Evaluating sheep hemoglobins with MD simulations as an animal model for sickle cell disease

Sickle cell disease (SCD) affects millions worldwide, yet there are few therapeutic options. To develop effective treatments, preclinical models that recapitulate human physiology and SCD pathophysiology are needed. SCD arises from a single Glu-to-Val substitution at position 6 in the β subunit of hemoglobin (Hb), promoting Hb polymerization and subsequent disease. Sheep share important physiological and developmental characteristics with humans, including the same developmental pattern of fetal to adult Hb switching. Herein, we investigated whether introducing the SCD mutation into the sheep β-globin locus would recapitulate SCD’s complex pathophysiology by generating high quality SWISS-MODEL sheep Hb structures and performing MD simulations of normal/sickle human (huHbA/huHbS) and sheep (shHbB/shHbS) Hb, establishing how accurately shHbS mimics huHbS behavior. shHbS, like huHbS, remained stable with low RMSD, while huHbA and shHbB had higher and fluctuating RMSD. shHbB and shHbS also behaved identically to huHbA and huHbS with respect to β2-Glu6 and β1-Asp73 (β1-Asn72 in sheep) solvent interactions. These data demonstrate that introducing the single SCD-causing Glu-to-Val substitution into sheep β-globin causes alterations consistent with the Hb polymerization that drives RBC sickling, supporting the development of a SCD sheep model to pave the way for alternative cures for this debilitating, globally impactful disease.

Design of potential anti-cancer agents as COX-2 inhibitors, using 3D-QSAR modeling, molecular docking, oral bioavailability proprieties, and molecular dynamics simulation.

Modeling the structural properties of novel morpholine-bearing 1, 5-diaryl-diazole derivatives as potent COX-2 inhibitor, two proposed models based on CoMFA and CoMSIA were evaluated by external and internal validation methods. Partial least squares analysis produced statistically significant models with Q 2 values of 0.668 and 0.652 for CoMFA and CoMSIA, respectively, and also a significant non-validated correlation coefficient R² with values of 0.882 and 0.878 for CoMFA and CoMSIA, respectively. Both models met the requirements of Golbraikh and Tropsha, which means that both models are consistent with all validation techniques. Analysis of the CoMFA and CoMSIA contribution maps and molecular docking revealed that the R1 substituent has a very significant effect on their biological activity. The most active molecules were evaluated for their thermodynamic stability by performing MD simulations for 100 ns; it was revealed that the designed macromolecular ligand complex with 3LN1 protein exhibits a high degree of structural and conformational stability. Based on these results, we predicted newly designed compounds, which have acceptable oral bioavailability properties and would have high synthetic accessibility.

Layering of hydroxyl groups causes anisotropic molecular clustering in liquid ethanol on hydrophobic surfaces: A molecular dynamics study

The clustering of hydrogen-bonding molecules in liquid is ubiquitous and closely related to the various properties of the liquid. At the solid–liquid interface, the influence of solid surfaces on the interfacial structure of hydrogen-bonding clusters, which has remained underexplored, is key to controlling the interfacial properties of the liquids. In this study, we performed MD simulations to reveal the interfacial structures of ethanol clusters present on hydrophobic solid surfaces. The number density profile of the hydroxyl groups indicated the presence of a layered structure, and the orientation of the hydrogen bonds (HBs) differed between the layers. The ethanol molecules preferred the lateral HBs in the layers enriched with hydroxyl groups, whereas the perpendicular HBs were dominant in the interlayer regions with fewer hydroxyl groups. Analysis of the aspect ratio of the clusters revealed that the hydrophobic surface induced the formation of longer interfacial ethanol clusters in the lateral direction, even when the hydroxyl groups of the ethanol molecules were oriented perpendicular to the surface. The lateral HBs in the enriched regions connected with each other, whereas the perpendicular ones in the interlayer regions did not, resulting in the lateral clustering of the ethanol molecules.

Exploring potential Plasmodium kinase inhibitors: a combined docking, MD and QSAR studies

Malaria is a disease caused mostly by Plasmodium falciparum, affects millions of people each year. The kinases are validated targets for malaria infection. In this study, we investigate for real and hypothetical compounds that can inhibit cyclic guanosine monophosphate (CGMP)-dependent protein kinase using molecular docking via combined similarity analysis, molecular dynamics simulations, quantitative structure activity relationship (QSAR). Using Tanimoto similarity scores, ∼8.4 million compounds were screened. Compounds that have at least 70% similarity are used in further analysis. These compounds are assessed by means of docking, MMBPSA, MMGBSA and ANI_LIE. Based on consensus of different free energy methods and docking we revealed two potential inhibitors that can be useful for treatment of malaria. Apart from screening of real compounds, we have also selected the 10 most plausible hypothetical compounds by performing QSAR. By QSAR proposed pharmacophores, we generated over 247 hypothetical compounds and among them 19 molecules with lower QSAR predicted IC50 values and high docking scores were selected for further analysis. We selected the top 10 inhibitor candidates and performed MD simulations for free energy calculations like the protocol applied for real compounds. According to the free energy calculations, we suggest 2 real (C34H29F5N8O4S and C30H27F2N7O2S2, PubChem IDs: 140564801 and 89035196, respectively) and 2 hypothetical (C23H27FN6O2S, MOL3 and C23H25FN6O2S, MOL4) compounds that can be effective inhibitors against the protein kinase of Plasmodium falciparum. Communicated by Ramaswamy H. Sarma

Computational analysis of sodium-dependent phosphate transporter SLC20A1/PiT1 gene identifies missense variations C573F, and T58A as high-risk deleterious SNPs

SLC20A1/PiT1 is a sodium-dependent inorganic phosphate transporter, initially recognized as the retroviral receptor for Gibbon Ape Leukemia Virus in humans. SNPs in SLC20A1 is associated with Combined Pituitary Hormone Deficiency and Sodium Lithium Counter transport. Using in silico techniques, we have screened the nsSNPs for their deleterious effect on the structure and function of SLC20A1. Screening with sequence and structure-based tools on 430 nsSNPs, filtered 17 nsSNPs which are deleterious. To evaluate the role of these SNPs, protein modeling and MD simulations were performed. A comparative analysis of model generated with SWISS-MODEL and AlphaFold shows that many residues are in the disallowed region of Ramachandran plot. Since SWISS-MODEL structure has a 25-residue deletion, the AlphaFold structure was used to perform MD simulation for equilibration and structure refinement. Further, to understand perturbation of energetics, we performed in silico mutagenesis and ΔΔG calculation using FoldX on MD refined structures, which yielded SNPs that are neutral (3), destabilizing (12) and stabilizing (2) on protein structure. Furthermore, to elucidate the impact of SNPs on structure, we performed MD simulations to discern the changes in RMSD, Rg, RMSF and LigPlot of interacting residues. RMSF profiles of representative SNPs revealed that A114V (neutral) and T58A (positive) were more flexible & C573F (negative) was more rigid compared to wild type, which is also reflected in the changes in number of local interacting residues in LigPlot and ΔΔG. Taken together, our results show that SNPs can lead to structural perturbations and impact the function of SLC20A1 with potential implications for disease. Communicated by Ramaswamy H. Sarma

Modeling the SARS-CoV-2 receptor ACE2 indicates that protein-bound Zn affects distant protein stability and interactions

Abstract Molecular Dynamics (MD) is a widely used drug design tool capable of rapidly screening the binding capacity of many candidate inhibitors in a cost-effective manner. This approach has been leveraged to search for molecules that can bind to angiotensin converting enzyme 2 (ACE2) and prevent SARS-CoV-2 viral entry to host cells. However, ACE2 is difficult to model due to an embedded zinc ion (Zn), which introduces complex charge transfer and polarization. Since the embedded Zn is distant from the site of ACE2 binding, many groups have assumed Zn does not impact protein interactions and have excluded Zn while modeling ACE2. Here, we evaluated the impact of Zn by performing MD simulations of Zn-bound and Zn-free versions of the ACE2-spike protein (S1) and ACE2-monoclonal antibody (mAb) systems . We found that excluding Zn had a significant effect on total protein stability and the stability of interacting residues, indicating that Zn can impact distant protein sites. Additionally, we discovered that including protein-bound Zn in MD simulations improved the binding free energy of both systems by −3.26 and −14.8 kcal/mol in the ACE2-S1 and ACE2-mAb systems, respectively. These data suggest that excluding Zn may alter inhibitor selection decisions and should be included for accurate modeling. Interestingly, ACE2-mAb is particularly sensitive to changes in receptor structure, likely reflecting its generation against in vivo Zn-bound ACE2. Collectively, our data demonstrates that excluding Zn significantly impacts MD simulation outcomes which inform inhibitor selection, particularly when modeling receptor-mAb complexes.

NanoLuc tandem repeats show misfolding during thermal denaturation which is reversible by E. coli chaperones (DnaK/DnaJ/GrpE).

Monomeric NanoLuc (Nluc) is a thermally robust bioluminescent protein with its thermal denaturation temperature at 58oC. In order to further examine this thermal behavior, we developed three protein constructs (monomeric, dyad, and triad Nluc). Interestingly, thermal denaturation experiments at 58oC showed sudden decrease in thermal stability when Nluc was linked to itself, dyad and triad Nluc constructs, while monomeric Nluc remained mostly folded under same conditions. Also, all three constructs maintained their activity (bioluminescence) when brought back to room temperature with no spontaneous recovery observed. However, when we examined the E. coli DnaK/DnaJ/GrpE chaperone system effect on this loss of thermal stability in refolding assays, we observed recovery in bioluminescence signal up to 70% for the poly-Nluc constructs. This observation strongly supports poly-Nluc is a strong chaperone substrate. Another interesting observation was that the refolding of these poly-Nluc constructs was possible at similar percentages even in the absence of GrpE showing a deviation from the canonical chaperone mechanism described up to now in literature. However, high GrpE concentrations were inhibitory to the protein refolding. Similarly, addition of disaggregase ClpB chaperone, showed no further assistance in refolding of the proteins and in some cases proved to be inhibiting the refolding. Lastly, we performed MD simulations of thermally unfolded and refolded monomeric and poly-Nluc constructs. These show that monomeric Nluc is able to correctly refold, while dyad Nluc misfolds with 78% and triad Nluc misfolds with 63%. Also, additional MD simulations suggest the reason of dyad and triad Nluc constructs misfolding is due to domain swapping preventing the correct refolding of these two constructs during thermal renaturation.

Atomistic insight into the essential binding event of ACE2-derived peptides to the SARS-CoV-2 spike protein.

The pathogenic agent of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) enters into human cells through the interaction between the receptor binding domain (RBD) of its spike glycoprotein and the angiotensin-converting enzyme 2 (ACE2) receptor. Efforts have been made towards finding antivirals that block thisinteraction, therefore preventing infection. Here, we determined the binding affinity of ACE2-derived peptides to the RBD of SARS-CoV-2 experimentally and performed MD simulations in order to understand key characteristics of their interaction. One of the peptides, p6, binds to the RBD of SARS-CoV-2 with nM affinity. Although the ACE2-derived peptides retain conformational flexibility when bound to SARS-CoV-2 RBD, we identified residues T27 and K353 as critical anchors mediating the interaction. New ACE2-derived peptides were developed based on the p6-RBD interface analysis and expecting the native conformation of the ACE2 to be maintained. Furthermore, we found a correlation between the helicity in trifluoroethanol and the binding affinity to RBD of the new peptides. Under the hypothesis that the conservation of peptide secondary structure is decisive to the binding affinity, we developed a cyclized version of p6 which had more helicity than p6 and approximately half of its KD value.

Antiviral activities of natural compounds and ionic liquids to inhibit the Mpro of SARS-CoV-2: a computational approach.

The recalcitrant spread of the COVID-19 pandemic produced by the novel coronavirus SARS-CoV-2 is one of the most destructive occurrences in history. Despite the availability of several effective vaccinations and their widespread use, this line of immunization often faces questions about its long-term efficacy. Since coronaviruses rapidly change, and multiple SARS-CoV-2 variants have emerged around the world. Therefore, finding a new target-based medication became a priority to prevent and control COVID-19 infections. The main protease (Mpro) is a salient enzyme in coronaviruses that plays a vital role in viral replication, making it a fascinating therapeutic target for SARS-CoV-2. We screened 0.2 million natural products against the Mpro of SARS-CoV-2 using the Universal Natural Product Database (UNPD). As well, we studied the role of ionic liquids (ILs) on the structural stabilization of Mpro. Cholinium-based ILs are biocompatible and used for a variety of biomedical applications. Molecular docking was employed for the initial screening of natural products and ILs against Mpro. To predict the drug-likeness features of lead compounds, we calculated the ADMET properties. We performed MD simulations for the selected complexes based on the docking outcomes. Using MM/PBSA approaches, we conclude that compounds NP-Hit2 (−25.6 kcal mol−1) and NP-Hit3 (−25.3 kcal mol−1) show stronger binding affinity with Mpro. The hotspot residues of Thr25, Leu27, His41, Met49, Cys145, Met165, and Gln189 strongly interacted with the natural compounds. Furthermore, naproxenate, ketoprofenate, and geranate, cholinium-based ILs strongly interact with Mpro and these ILs have antimicrobial properties. Our findings will aid in the development of effective Mpro inhibitors.

Identifying the Hot Spot Residues of the SARS-CoV-2 Main Protease Using MM-PBSA and Multiple Force Fields.

In this study, we investigated the binding affinities between the main protease of SARS-CoV-2 virus () and its various ligands to identify the hot spot residues of the protease. To benchmark the influence of various force fields on hot spot residue identification and binding free energy calculation, we performed MD simulations followed by MM-PBSA analysis with three different force fields: CHARMM36, AMBER99SB, and GROMOS54a7. We performed MD simulations with 100 ns for 11 protein–ligand complexes. From the series of MD simulations and MM-PBSA calculations, it is identified that the MM-PBSA estimations using different force fields are weakly correlated to each other. From a comparison between the force fields, AMBER99SB and GROMOS54a7 results are fairly correlated while CHARMM36 results show weak or almost no correlations with the others. Our results suggest that MM-PBSA analysis results strongly depend on force fields and should be interpreted carefully. Additionally, we identified the hot spot residues of , which play critical roles in ligand binding through energy decomposition analysis. It is identified that the residues of the S4 subsite of the binding site, N142, M165, and R188, contribute strongly to ligand binding. In addition, the terminal residues, D295, R298, and Q299 are identified to have attractive interactions with ligands via electrostatic and solvation energy. We believe that our findings will help facilitate developing the novel inhibitors of SARS-CoV-2.

Application of in vitro PAMPA technique and in silico computational methods for blood-brain barrier permeability prediction of novel CNS drug candidates

Permeability assessment of small molecules through the blood-brain barrier (BBB) plays a significant role in the development of effective central nervous system (CNS) drug candidates. Since in vivo methods for BBB permeability estimation require a lot of time and resources, in silico and in vitro approaches are becoming increasingly popular nowadays for faster and more economical predictions in early phases of drug discovery. In this work, through application of in vitro parallel artificial membrane permeability assay (PAMPA-BBB) and in silico computational methods we aimed to examine the passive permeability of eighteen compounds, which affect serotonin and dopamine levels in the CNS. The data set was consisted of novel six human dopamine transporter (hDAT) substrates that were previously identified as the most promising lead compounds for further optimisation to achieve neuroprotective effect, twelve approved CNS drugs, and their related compounds. Firstly, PAMPA methods was used to experimentally determine effective BBB permeability (Pe) for all studied compounds and obtained results were further submitted for quantitative structure permeability relationship (QSPR) analysis. QSPR models were built by using three different statistical methods: stepwise multiple linear regression (MLR), partial least square (PLS), and support-vector machine (SVM), while their predictive capability was tested through internal and external validation. Obtained statistical parameters (MLR- R2pred=-0.10; PLS- R2pred=0.64, r2m=0.69, r/2m=0.44; SVM- R2pred=0.57, r2m=0.72, r/2m=0.55) indicated that the SVM model is superior over others. The most important molecular descriptors (H0p and SolvEMt_3D) were identified and used to propose structural modifications of the examined compounds in order to improve their BBB permeability. Moreover, steered molecular dynamics (SMD) simulation was employed to comprehensively investigate the permeability pathway of compounds through a lipid bilayer. Taken together, the created QSPR model could be used as a reliable and fast pre-screening tool for BBB permeability prediction of structurally related CNS compounds, while performed MD simulations provide a good foundation for future in silico examination.

Surface Corrugations and Layer Thickness Dependent Frictional Behavior of MoS2 – A Computational Study

2D materials are at the core of nano/micro-electro-mechanical systems (MEMS/NEMS). However, surface corrugations are unavoidable in 2D materials because of operational inefficiencies involved in the synthesis procedures. Engineering the mechanical properties of the 2D materials are highly sought-after because they are the driving mechanism behind the nanodevices' functionality. So far, most related works focus on single planar 2D materials, i.e., Graphene. The existing Transient Metal Dichalcogenide (TMD) analyses do not include torque implications on the frictional force and multiple different variables simultaneously. In this work, we have combined the two aspects, i.e., surface irregularities with the need for tuning the mechanical properties. We have studied tuning the frictional properties of Molybdenum Disulfide (MoS2) by reactive molecular dynamics (rMD) modeling, which is further analyzed by density functional theory (DFT) code. We analyzed BADER charge and molecular orbitals by DFT code. The MoS2 layer(s) are indented by using an in-built library in Large-scale Atomic/Molecular Massively Parallel Simulator (LAMMPS) to obtain different conformations of the system. We considered multiple cases, i.e., varying number of the layers (1-3), the number of dents (2-8), the radius of each dent (12-24 Å), and the pattern of the dents (in-line and zigzag). Next, we performed MD simulations to pass a hemispherical diamond probe across the indented surface to measure all spatial components of the reactional force and torque experienced by the probe during its movement. The probe is modeled by spring support on six axes to stabilize the movement. In total, 16 different systems are studied with different combinations of the dent's radius, pattern, quantity, and the number of layers. We hypothesize the frictional force experienced by the probe is affected by the materials’ geometry, both adjacent to and along the line of contact. Our torque plots validate our hypothesis. The major fluctuations in torque plots correlate with the fluctuations in force plots after neglecting the data noise. Our approach is useful for any other 2D materials. Our results provide insight into the characterization of the frictional dependence on locale surface corrugations.

Energetic and structural basis for the differences in infectivity between the wild-type and mutant spike proteins of SARS-CoV-2 in the Mexican population

SARS-CoV-2 is the causative agent of the ongoing viral pandemic of COVID-19. After the emergence of this virus, it became a global public health concern and quickly evolved into a pandemic. Mexico is currently in the third position in the number of deaths due to SARS-CoV-2. To date, there have been several lineages of SARS-CoV-2 worldwide; in the Mexican population, two variants of the spike protein (S-protein) are found, localized at H49Y and D614G, which have been related to increased infectivity with respect to the wild-type S-protein. To understand how these differences impact the structural behavior of the S-protein of SARS-CoV-2, as well as binding with ACE2, we performed MD simulations combined with the molecular mechanics generalized Born/Poisson-Boltzmann surface area (MMGB(PB)SA) approach starting from X-ray crystallography data. Energetic and structural analysis showed that the differences in infectivity can be explained by differences in affinity of the protein-protein interface between the wild-type and mutant S-protein with ACE2. Conformational analysis showed that molecular recognition between the S-protein and ACE2 is linked to a decrease in the conformational flexibility of wild-type and mutant S-protein; however, an increase in the conformational mobility of ACE2 could also contribute to the binding affinity observed using the MMGB(PB)SA method.

Structural, enzymatic and pharmacological profiles of AplTX-II - A basic sPLA2 (D49) isolated from the Agkistrodon piscivorus leucostoma snake venom

A basic sPLA2 (D49) from the venom of snake Agkistrodon piscivorus leucostoma (AplTX-II) was isolated, purified and characterized. We determined the enzymatic and pharmacological profiles of this toxin. AplTX-II was isolated with a high level of purity through reverse phase chromatography and molecular exclusion. The enzyme showed pI 9.48 and molecular weight of 14,003 Da. The enzymatic activity of the AplTX-II depended on Ca2+ pH and temperature. The comparison of the primary structure with other sPLA2s revealed that AplTX-II presented all the structural reasons expected for a basic sPLA2s. Additionally, we have resolved its structure with the docked synthetic substrate NOBA (4-nitro-3-octanoyloxy benzoic acid) by homology modeling, and performed MD simulations with explicit solvent. Structural similarities were found between the enzyme's modeled structure and other snake sPLA2 X-Ray structures, available in the PDB database. NOBA and active-site water molecules spontaneously adopted stable positions and established interactions in full agreement with the reaction mechanism, proposed for the physiological substrate, suggesting that NOBA hydrolysis is an excellent model to study phospholipid hydrolysis.

The Allosteric Effect in Antibody-Antigen Recognition.

We studied the molecular details of the recognition of antigens by the variable domain of their cognate antibodies in as well as those elicited by the constant domains, which do not directly interact with antigens. Such effects are difficult to study experimentally; however, molecular dynamics simulations and subsequent residue interaction network analysis provide insight into the allosteric communication between the antigen-binding CDR region and the constant domain. We performed MD simulations of the complex of Fab and prion-associated peptide in the apo and bound forms and follow the conformational changes in the antibody and cross-talk between its subunits and with antigens. These protocols could be generally applied for studies of other antigens-antibody recognition systems.

Effect of Different Salt Concentrations on Dimethyl Sulfoxide (DMSO) Nanocluster Structures by Molecular Dynamics Simulations.

We performed MD simulations to examine dimethyl sulfoxide (DMSO) nanocluster structures in NaCl aqueous solution with different concentrations (0.45 g/100 mL, 0.9 g/100 mL, 1.8 g/100 mL, 2.7 g/100 mL, and 3.6 g/100 mL). Results showed that interaction between Na+ and DMSO at the first solvation shells was weakened due to acceleration rotational influence of ion driven by NaCl concentration. We investigated the tetrahedral order parameter and average H-B number of water molecules. These results indicated that NaCl influenced the solvation structure of water cluster, but that of DMSO was not affected by NaCl. We also found that Na+ was prior solvated by water solution in these mixture systems, and Cl- only existed in the water cluster in our simulation systems. Consequently, we herein proposed a decentralized model that depicts microphysical structure images of DMSO in NaCl aqueous solution systems.

Understanding the impacts of self-shuffling approach on structure and function of shuffled endoglucanase enzyme via MD simulations

Abstract Objective We identify the impacts of structural differences on functionality of EG3_S2 endoglucanase enzyme with MD studies. The results of previous experimental studies have been explained in details with computational approach. The objective of this study is to explain the functional differences between shuffled enzyme (EG3_S2) and its native counterpart (EG3_nat) from Trichoderma reseei, via Molecular Dynamics approach. Materials and methods For this purpose, we performed MD simulations along 30 ns at three different reaction temperatures collected as NpT ensemble, and then monitored the backbone motion, flexibilities of residues, and intramolecular interactions of EG3_S2 and EG3_nat enzymes. Results According to MD results, we conclude that EG3_S2 and EG3_nat enzymes have unique RMSD patterns, e.g. RMSD pattern of EG3_S2 is more dynamic than that of EG3_nat at all temperatures. In addition to this dynamicity, EG3_S2 establishes more salt bridge interactions than EG3_nat. Conclusion By taking these results into an account with the preservation of catalytic Glu residues in a proper manner, we explain the structural basis of differences between shuffled and native enzyme via molecular dynamic studies.