The Impact of Using Single Atomistic Long-Range Cutoff Schemes with the GROMOS 54A7 Force Field

Delivery of rapamycin by biomimetic peptide nanoparticles targeting oxidized low-density lipoprotein in atherosclerotic plaques

Drug delivery systems based on biomimetic peptide nanoparticles are steadily gaining prominence in the treatment of diverse medical conditions. This study focused on the development of peptides that depend on ligand-receptor interactions to load rapamycin (RAPA). Furthermore, a multifunctional peptide was engineered to target oxidized low-density lipoprotein (oxLDL) within atherosclerotic plaques, facilitating the localized delivery of RAPA. The interactions between peptides and RAPA/oxLDL were analyzed by simulations and experimental approaches. Results show that the main amino acid residues on the mammalian target of rapamycin that bind to RAPA are constructed as peptides (P1 and P2), which have specific interactions with RAPA and can effectively improve the loading efficiency of RAPA. The encapsulation and drug loading efficiencies of P1/P2 were 68.0/47.9% and 48.3/36.5%, respectively. In addition, the interaction force of the multifunctional peptide (P3) and oxLDL surpassed that of their interaction with human umbilical vein endothelial cells by a factor of 3.6, conclusively establishing the specific targeting of oxLDL by these nanoparticles. The encapsulation and drug loading efficiencies of P3 for RAPA were determined to be 60.2% and 41.5%. P3 can effectively load RAPA and target oxLDL within the plaque, suggesting that P3 has potential as a therapeutic agent for atherosclerotic disease.

Models of the Three-Component Bilayer of Stratum Corneum: A Molecular Simulation Study

The construction of the stratum corneum (SC) is crucial to the problems of transdermal drug delivery. SC consists of the keratinocyte layers and the lipid matrix surrounding it. Among them, the lipid matrix is the barrier for many exogenous molecules, mainly composed of ceramides (CERs), free fatty acids (FFA), and cholesterol (CHOL). In this work, we developed single-component (CERs, CER-NS, and CER-EOS) and six three-component models, and each model was simulated by using the GROMOS-54A7 force field. Short-period phase (SPP) and long-period phase (LPP) systems were established separately, and area per lipid (APL), thickness, order of carbon chain (SCD), and density distribution were analyzed. The transition of CER-NS and CER-EOS in LPP was observed. The results of hydrogen bonds in the lipid systems indicated that a strong hydrogen-bond network was formed between the skin-lipid bilayers. Umbrella sampling method simulations were performed to calculate the free energy change of ethanol moving into the skin-lipid bilayer. The results revealed that ethanol molecules pulled some water molecules into the membrane when they passed through SPP-1. Our findings provided some insights and models of the stratum corneum that could be used for the subsequent mechanism of macromolecule permeation through membranes in drugs, cosmetics, and so on.

High Charge Density in Peptide Dendrimers is Required to Destabilize Membranes: Insights into Endosome Evasion

Peptide dendrimers are a type of branched, symmetric, and topologically well-defined molecule that have already been used as delivery systems for nucleic acid transfection. Several of the most promising sequences showed high efficiency in many key steps of transfection, namely, binding siRNA, entering cells, and evading the endosome. However, small changes to the peptide dendrimers, such as in the hydrophobic core, the amino acid chirality, or the total available charges, led to significantly different experimental results with unclear mechanistic insights. In this work, we built a computational model of several of those peptide dendrimers (MH18, MH13, and MH47) and some of their variants to study the molecular details of the structure and function of these molecules. We performed CpHMD simulations in the aqueous phase and in interaction with a lipid bilayer to assess how conformation and protonation are affected by pH in different environments. We found that while the different peptide dendrimer sequences lead to no substantial structural differences in the aqueous phase, the total charge and, more importantly, the total charge density are key for the capacity of the dendrimer to interact and destabilize the membrane. These dendrimers become highly charged when the pH changes from 7.5 to 4.5, and the presence of a high charge density, which is decreased for MH47 that has four fewer titratable lysines, is essential to trigger membrane destabilization. These findings are in excellent agreement with the experimental data and help us to understand the high efficiency of some dendrimers and why the dendrimer MH47 is unable to complete the transfection process. This evidence provides further understanding of the mode of action of these peptide dendrimers and will be pivotal for the future design of new sequences with improved transfection capabilities.

A molecular dynamics simulation study of glycine/serine octapeptides labeled with 2,3-diazabicyclo[2.2.2]oct-2-ene fluorophore

The compound 2,3-diazabicyclo[2.2.2]oct-2-ene (DBO) is a versatile fluorophore widely used in Förster resonance energy transfer (FRET) spectroscopy studies due to its remarkable sensitivity, enabling precise donor-acceptor distance measurements, even for short peptides. Integrating time-resolved and FRET spectroscopies with molecular dynamics simulations provides a robust approach to unravel the structure and dynamics of biopolymers in a solution. This study investigates the structural behavior of three octapeptide variants: Trp-(Gly-Ser)3-Dbo, Trp-(GlyGly)3-Dbo, and Trp-(SerSer)3-Dbo, where Dbo represents the DBO-containing modified aspartic acid, using molecular dynamics simulations. Glycine- and serine-rich amino acid fragments, common in flexible protein regions, play essential roles in functional properties. Results show excellent agreement between end-to-end distances, orientational factors from simulations, and the available experimental and theoretical data, validating the reliability of the GROMOS force field model. The end-to-end distribution, modeled using three Gaussian distributions, reveals a complex shape, confirmed by cluster analysis highlighting a limited number of significant conformations dominating the peptide landscape. All peptides predominantly adopt a disordered state in the solvent, yet exhibit a compact shape, aligning with the model of disordered polypeptide chains in poor solvents. Conformations show marginal dependence on chain composition, with Ser-only chains exhibiting slightly more elongation. This study enhances our understanding of peptide behavior, providing valuable insights into their structural dynamics in solution.

Tailored horseshoe-shaped nicotinonitrile scaffold as dual promising c-Met and Pim-1 inhibitors: Design, synthesis, SAR and in silico study

For the horseshoe tactic to succeed in inhibiting c-Met and Pim-1, the nicotinonitrile derivatives (2a-n) were produced in high quantities by coupling acetyl phenylpyrazole (1) with the proper aldehydes and ethyl cyanoacetate under basic conditions. Consistent basic and spectroscopic data (NMR, IR, Mass, and HPLC) supported the new products' structural findings. With IC50 potency in nanomolar ranges, these compounds had effectively repressed them, particularly compounds 2d and 2 h, with IC50 values below 200 nM. The most potent compounds (2d and 2 h) were tested for their antitumor effects against prostate (PC-3), colon (HCT-116), and breast (MDA-MB-231) and were evaluated in comparison to the anticancer drug tivantinib using the MTT assay. Similar to tivantinib, these compounds showed good antiproliferative properties against the HCT-116 tumor cells while having low cytotoxicity towards healthy fetal colon (FHC) cells. In the HCT-116 cell line, their ability to trigger the apoptotic cascade was also investigated by looking at the level of Bax and Bcl-2 as well as the activation of the proteolytic caspase cascade. When HCT-116 cells were exposed to compounds 2d and 2 h in comparison to the control, active caspase-3 levels increased. The HCT-116 cell line also upregulated Bcl-2 protein levels and downregulated Bax levels. Additionally, when treated with compound 2d, the HCT-116 cell cycle was primarily stopped at the S phase. Compared to the control, compound 2d treatment significantly inhibited the protein expression levels of c-Met and Pim-1 kinases in the treated HCT-116 cells. Thorough molecular modeling analyses, such as molecular docking and dynamic simulation, were performed to ascertain the binding mechanism and stability of the target compounds.

Computational identification of candidate inhibitors for Dihydrofolate reductase in Acinetobacter baumannii

Acinetobacter baumannii is one of the emerging causes of hospital acquired infections and this bacterium, due to multi-drug resistant and Extensive Drug resistant has been able to develop resistance against the antimicrobial agents that are being used to eliminate it. A.baumannii has been the cause of death in immune compromised patients in hospitals. Hence it is the urgent need of time to find potential inhibitors for this bacterium to cease its virulence and affect its survival inside host organisms. The Dihydrofolate reductase enzyme, which is an important biocatalyst in the conversion of Dihydrofolate to Tetrahydrofolate, is an important drug target protein. In the present study high throughput screening is used to identify the inhibitors of this enzyme. The prioritized ligand molecular candidates identified through virtual screening for the substrate binding site of the predicted model are Z1447621107, Z2604448220 and Z1830442365. The Molecular Dynamics Simulation study suggests that potential inhibitor of the Dihydrofolate reductase enzyme would prevent bacteria from completing its life cycle, affecting its survival. Finally the complexes were analysed for binding free energy of the Dihydrofolate reductase enzyme complexes with the ligands.

Insights into the conformational, secondary structural, dynamical and hydration pattern changes of glucose mediated glycated HSA: a molecular dynamics approach

The robust structural nature of human serum albumin (HSA) is responsible for its multifarious functional property. The site specific glycation of HSA due to hyperglycaemia (excess glucose) causes structural changes which have an impact on the functioning of the protein. This work investigates the effects of glucose-mediated glycation in the altered inter-domain motion, distorted binding site conformation and modified hydration patterns, Trp214 orientation, and secondary structure transition using simulation approach. Here we have observed an increase of turns in the helices of glycated HSA, which modulates the open-close conformation of Sudlow I & II. The secondary structure changes of glycated HSA indicate plausible reduction in the alpha helical content in the helices which participates in ligand binding. It also affects geometrical features of drug binding sites (Sudlow I and II) such as volume and hydration. We found that glycation disturbs domain specific mobility patterns of HSA, a substantial feature for albumin drug binding ability which is also correlated with changes in the local environment of Trp214.Communicated by Ramaswamy H. Sarma.

The Power of Molecular Dynamics Simulations and Their Applications to Discover Cysteine Protease Inhibitors

A large family of enzymes with the function of hydrolyzing peptide bonds, called peptidases or cysteine proteases (CPs), are divided into three categories according to the peptide chain involved. CPs catalyze the hydrolysis of amide, ester, thiol ester, and thioester peptide bonds. They can be divided into several groups, such as papain-like (CA), viral chymotrypsin-like CPs (CB), papainlike endopeptidases of RNA viruses (CC), legumain-type caspases (CD), and showing active residues of His, Glu/Asp, Gln, Cys (CE). The catalytic mechanism of CPs is the essential cysteine residue present in the active site. These mechanisms are often studied through computational methods that provide new information about the catalytic mechanism and identify inhibitors. The role of computational methods during drug design and development stages is increasing. Methods in Computer-Aided Drug Design (CADD) accelerate the discovery process, increase the chances of selecting more promising molecules for experimental studies, and can identify critical mechanisms involved in the pathophysiology and molecular pathways of action. Molecular dynamics (MD) simulations are essential in any drug discovery program due to their high capacity for simulating a physiological environment capable of unveiling significant inhibition mechanisms of new compounds against target proteins, especially CPs. Here, a brief approach will be shown on MD simulations and how the studies were applied to identify inhibitors or critical information against cysteine protease from several microorganisms, such as Trypanosoma cruzi (cruzain), Trypanosoma brucei (rhodesain), Plasmodium spp. (falcipain), and SARS-CoV-2 (Mpro). We hope the readers will gain new insights and use our study as a guide for potential compound identifications using MD simulations.

Conformational variation of site specific glycated albumin: A Molecular dynamics approach

Human serum albumin (HSA) is a major cargo protein, which undergoes glycation in hyperglycaemic conditions and results in impaired function. In physiological conditions, HSA plays a crucial role in pharmacological activities such as drug transport or delivery through its binding capacity and also by its enzymatic activity, which enables the translation of pro-drugs into active drugs. In this study, the impact of the methylglyoxal-mediated glycation on dynamic behaviour of inter-domain motion, Cys34 reactivity, binding site residual interaction and secondary structure transition were investigated through molecular dynamics simulation. The alteration in inter-domain motion reflects the effect of glycation-mediated changes on the structural conformation of albumin. The binding site residue interactions and volume analysis revealed the impact of glycation on the geometry of the binding site. We also found the correlation of Cys34 reactivity with increase of turns in the region between Ia-h4 and Ia-h5. The rise in turn formation in that region keeps Tyr84 farther away from Cys34 which could lead to higher Cys34 reactivity. In parallel, significant alterations in alpha helical content of helices in the binding sites were observed. These structural and conformational changes in glycated albumin could be the causative agents for functional impairment which leads to diabetic complications.

Papaverinol-N-Oxide: A Microbial Biotransformation Product of Papaverine with Potential Antidiabetic and Antiobesity Activity Unveiled with In Silico Screening

Bioconversion of biosynthetic heterocyclic compounds has been utilized to produce new semisynthetic pharmaceuticals and study the metabolites of bioactive drugs used systemically. In this investigation, the biotransformation of natural heterocyclic alkaloid papaverine via filamentous fungi was explored. Molecular docking simulations, using protein tyrosine phosphatase 1B (PTP1B), α-glucosidase and pancreatic lipase (PL) as target enzymes, were performed to investigate the antidiabetic potential of papaverine and its metabolites in silico. The metabolites were isolated from biotransformation of papaverine with Cunninghamella elegans NRRL 2310, Rhodotorula rubra NRRL y1592, Penicillium chrysogeneum ATCC 10002 and Cunninghamella blackesleeana NRRL 1369 via reduction, demethylation, N-oxidation, oxidation and hydroxylation reactions. Seven metabolites were isolated: namely, 3,4-dihydropapaverine (metabolite 1), papaveroline (metabolite 2), 7-demethyl papaverine (metabolite 3), 6,4'-didemethyl papaverine (metabolite 4), papaverine-3-ol (metabolite 5), papaverinol (metabolite 6) and papaverinol N-oxide (metabolite 7). The structural elucidation of the metabolites was investigated with 1D and 2D NMR and mass spectroscopy (EI and ESI). The molecular docking studies showed that metabolite 7 exhibited better binding interactions with the target enzymes PTP1B, α-glucosidase and PL than did papaverine. Furthermore, papaverinol-N-oxide (7) also displayed inhibition of α-glucosidase and lipase enzymes comparable to that of their ligands (acarbose and orlistat, respectively), as unveiled with an in silico ADMET profile, molecular docking and molecular dynamics studies. In conclusion, this study provides evidence for enhanced inhibition of PTP1B, α-glucosidase and PL via some papaverine fungal transformation products and, therefore, potentially better antidiabetic and antiobesity effects than those of papaverine and other known therapeutic agents.

Glycation restrains open-closed conformation of Insulin

In hyperglycemic conditions, the level of reactive dicarbonyl metabolites concentration is found to be high, which plays a significant role in protein glycation. Despite decades of research, the effect of methylglyoxal on the structure and function of insulin is still unknown. Through a shift in conformation at the B-chain C-terminal (BT-CT) hinge from an "open" to a "wide-open" conformation, insulin binds to the receptor and activates the signal cascade. Insulin resistance, which is the main sign of Type 2 Diabetes, can be caused by a lack of insulin signaling. Methylglyoxal site-specific glycation in residue R22 at B chain forms AGE product Methylglyoxal-hydroimidazolone (MGH1) in insulin. In this work, we present molecular dynamics study of this glycated insulin R22MGH1, which revealed new insights into the conformational and structural changes. We find the following key results: 1) B-chain in insulin undergoes a closed conformational change upon glycation. 2) Glycated insulin shows secondary structure alteration. 3) Glycated insulin retains its closed shape due to an unusually strong hydrophobic contact between B-chain residues. 4) Wide open native conformation of insulin allows the B chain helix to be surrounded by more water molecules compared to the closed conformation of glycated insulin. The closed conformation of glycated insulin impairs its binding to insulin receptor (IR).

Marmesin and Marmelosin Interact with the Heparan Sulfatase-2 Active Site: Potential Mechanism for Phytochemicals from Bael Fruit Extract as Antitumor Therapeutics

Human heparan sulfatase-2 (HSULF-2) is an oncoprotein overexpressed in the surface of all types of tumor cells and its activity plays a critical role in cancer survival and progression. Our previous studies have shown that bael fruit extract, containing marmesin and marmelosin, inhibits the HSULF-2 activity and kills breast tumor cells, but the mechanism of these processes remains fairly known mainly because the HSULF-2's 3D structure is partially known. Herein, we aimed at providing an in silico molecular mechanism of the inhibition of human HSULF-2 by phytochemicals from bael fruit extract. Pharmacokinetic parameters of the main phytochemicals contained in the bael fruit extract, sequence-based 3D structure of human HSULF-2, and the interaction of bael fruit's phytochemicals with the enzyme active site was modeled, evaluated, and verified. Docking studies revealed marmesin and marmelosin as potential inhibitors with binding score -8.5 and -7.7 Kcal/mol; these results were validated using molecular dynamics simulations, which exhibited higher stability of the protein-ligand complexes. Taking together, with our earlier in vitro data, our computational analyses suggest that marmesin and marmelosin interact at the active site of HSULF-2 providing a potential mechanism for its inhibition and consequent antitumor activity by phytochemicals contained in the bael fruit extract.

Increasing the Realism of in Silico pHLIP Peptide Models with a Novel pH Gradient CpHMD Method

The pH-low insertion peptides (pHLIP) are pH-dependent membrane inserting peptides, whose function depends on the cell microenvironment acidity. Several peptide variants have been designed to improve upon the wt-sequence, particularly the state transition kinetics and the selectivity for tumor pH. The variant 3 (Var3) peptide is a 27 residue long peptide, with a key titrating residue (Asp-13) that, despite showing a modest performance in liposomes (pK^ins ∼ 5.0), excelled in tumor cell experiments. To help rationalize these results, we focused on the pH gradient in the cell membrane, which is one of the crucial properties that are not present in liposomes. We extended our CpHMD-L method and its pH replica-exchange (pHRE) implementation to include a pH gradient and mimic the pHLIP-membrane microenvironment in a cell where the internal pH is fixed (pH 7.2) and the external pH is allowed to change. We showed that, by properly modeling the pH-gradient, we can correctly predict the experimentally observed loss and gain of performance in tumor cells experiments by the wt and Var3 sequences, respectively. In sum, the pH gradient implementation allowed for more accurate and realistic pK_a estimations and was a pivotal step in bridging the in silico data and the in vivo cell experiments.

Real-time fluorescence dynamics in one-step synthesis of gold nanoclusters coupling with peptide motifs

The molecule-like electronic structure endows gold nanoclusters (AuNCs) a most intriguing property, fluorescence, thereby AuNCs offer a great potential for biomedical applications. Recent efforts to improve the fluorescence of AuNCs mainly focus on tailoring size, structure and chemical environments. Herein, with the help of molecular dynamics simulation, we designed tyrosine-containing peptide motifs as the reducing agents, protecting ligands to synthesis P (peptide)-AuNCs in one-step reaction, which was developed to real-time monitor the fluorescence evolution of P-AuNCs. P-AuNCs with a quantum yield of ∼ 18 % were synthesized and further demonstrated for multiple biomedical applications, such as sensing of temperature (10-55 ℃) and metal ions (with a limit of detection of 5 nM for Hg2+), as well as cell labeling and imaging. With the excellent biocompatibility, wide spectral range and potential capacity for bio-recognition, this study provides a useful one-step synthesis strategy for screening out peptide motifs to real-time modulate the optical properties of peptide-containing hybrid nanomaterials.

Extending the Stochastic Titration CpHMD to CHARMM36m

The impact of pH on proteins is significant but often neglected in molecular dynamics simulations. Constant-pH Molecular Dynamics (CpHMD) is the state-of-the-art methodology to deal with these effects. However, it still lacks widespread adoption by the scientific community. The stochastic titration CpHMD is one of such methods that, until now, only supported the GROMOS force field family. Here, we extend this method's implementation to include the CHARMM36m force field available in the GROMACS software package. We test this new implementation with a diverse group of proteins, namely, lysozyme, Staphylococcal nuclease, and human and E. coli thioredoxins. All proteins were conformationally stable in the simulations, even at extreme pH values. The RMSE values (pK_a prediction vs experimental) obtained were very encouraging, in particular for lysozyme and human thioredoxin. We have also identified a few residues that challenged the CpHMD simulations, highlighting scenarios where the method still needs improvement independently of the force field. The CHARMM36m all-atom implementation was more computationally efficient when compared with the GROMOS 54A7, taking advantage of a shorter nonbonded interaction cutoff and a less frequent neighboring list update. The new extension will allow the study of pH effects in many systems for which this force field is particularly suited, i.e., proteins, membrane proteins, lipid bilayers, and nucleic acids.

Molecular insights on bioactive compounds againstCovid-19: A Network pharmacological and computational study

BACKGROUND

Network pharmacology based identification of phytochemicals in the form of cocktails against off-targets can play a significant role in inhibition of SARS_CoV2 viral entry and its propagation. This study includes network pharmacology, virtual screening, docking and molecular dynamics to investigate the distinct antiviral mechanisms of effective phytochemicals against SARS_CoV2.

METHODS

SARS_CoV2 human-protein interaction network was explored from the BioGRID database and analysed using Cytoscape. Further analysis was performed to explore biological function, protein-phytochemical/drugs network and up-down regulation of pathological host target proteins. This lead to understand the antiviral mechanism of phytochemicals against SARS_CoV2. The network was explored through g:Profiler, EnrichR, CTD, SwissTarget, STITCH, DrugBank, BindingDB, STRING and SuperPred. Virtual screening of phytochemicals against potential antiviral targets such as M-Pro, NSP1, Receptor binding domain, RNA binding domain, and ACE2 discloses the effective interaction between them. Further, the binding energy calculations through simulation of the docked complex explains the efficiency and stability of the interactions.

RESULTS

The network analysis identified quercetin, genistein, luteolin, eugenol, berberine, isorhamnetin and cinnamaldehyde to be interacting with host proteins ACE2, DPP4, COMT, TUBGCP3, CENPF, BRD2 and HMOX1 which are involved in antiviral mechanisms such as viral entry, viral replication, host immune response, and antioxidant activity. Thus indicating that herbal cocktails can effectively tackle the viral hijacking of the crucial biological functions of human host. Further exploration through Virtual screening, docking and molecular dynamics recognizes the effective interaction of phytochemicals such as punicalagin, scutellarin, and solamargine with their respective potential targets.

CONCLUSION

This work illustrates probable strategy for identification of phytochemical based cocktails and off-targets which are effective against SARS_CoV 2.

Optimization of an in Silico Protocol Using Probe Permeabilities to Identify Membrane Pan-Assay Interference Compounds

Membrane pan-assay interference compounds (PAINS) are a class of molecules that interact nonspecifically with lipid bilayers and alter their physicochemical properties. An early identification of these compounds avoids chasing false leads and the needless waste of time and resources in drug discovery campaigns. In this work, we optimized an in silico protocol on the basis of umbrella sampling (US)/molecular dynamics (MD) simulations to discriminate between compounds with different membrane PAINS behavior. We showed that the method is quite sensitive to membrane thickness fluctuations, which was mitigated by changing the US reference position to the phosphate atoms of the closest interacting monolayer. The computational efficiency was improved further by decreasing the number of umbrellas and adjusting their strength and position in our US scheme. The inhomogeneous solubility-diffusion model (ISDM) used to calculate the membrane permeability coefficients confirmed that resveratrol and curcumin have distinct membrane PAINS characteristics and indicated a misclassification of nothofagin in a previous work. Overall, we have presented here a promising in silico protocol that can be adopted as a future reference method to identify membrane PAINS.

Characterizing the potentially neuronal acetylcholinesterase reactivity toward chiral pyraclofos: Enantioselective insights from spectroscopy, in silico docking, molecular dynamics simulation and per-residue energy decomposition studies

Chiral organophosphorus agents are distributed ubiquitously in the environment, but the neuroactivity of these asymmetric chemicals to humans remains uncertain. This scenario was to explore the stereoselective neurobiological response of human acetylcholinesterase (AChE) to chiral pyraclofos at the enantiomeric scale, and then decipher the microscopic basis of enantioselective neurotoxicity of pyraclofos enantiomers. The results indicated that (R)-/(S)-pyraclofos can form the bioconjugates with AChE with a stoichiometric ratio of 1:1, but the neuronal affinity of (R)-pyraclofos (K = 6.31 × 10⁴ M^-1) with AChE was larger than that of (S)-pyraclofos (K = 1.86 × 10⁴ M^-1), and significant enantioselectivity was existed in the biochemical reaction. The modes of neurobiological action revealed that pyraclofos enantiomers were situated at the substrate binding domain, and the strength of the overall noncovalent bonds between (S)-pyraclofos and the residues was weaker than that of (R)-pyraclofos, resulting in the high inhibitory effect of (R)-pyraclofos toward the activity of AChE. Dynamic enantioselective biointeractions illustrated that the intervention of inherent conformational flexibility in the AChE-(R)-pyraclofos was greater than that of the AChE-(S)-pyraclofos, which arises from the big spatial displacement and the conformational flip of the binding domain composed of the residues Thr-64～Asn-89, Gly-122～Asp-134, and Thr-436～Tyr-449. Energy decomposition exhibited that the Gibbs free energies of the AChE-(R)-/(S)-pyraclofos were ΔG° = －37.4/－30.2 kJ mol^-1, respectively, and the disparity comes from the electrostatic energy during the stereoselective neurochemical reactions. Quantitative conformational analysis further confirmed the atomic-scale computational chemistry conclusions, and the perturbation of (S)-pyraclofos on the AChE's ordered conformation was lower than that of (R)-pyraclofos, which is germane to the interaction energies of the crucial residues, e.g. Tyr-124, Tyr-337, Asp-74, Trp-86, and Tyr-119. Evidently, this attempt will contribute mechanistic information to uncovering the neurobiological effects of chiral organophosphates on the body.

Improved Protocol to Tackle the pH Effects on Membrane-Inserting Peptides

Many important biological pathways rely on membrane-interacting peptides or proteins, which can alter the biophysical properties of the cell membrane by simply adsorbing to its surface to undergo a full insertion process. To study these phenomena with atomistic detail, model peptides have been used to refine the current computational methodologies. Improvements have been made with force-field parameters, enhanced sampling techniques to obtain faster sampling, and the addition of chemical-physical properties, such as pH, whose influence dramatically increases at the water/membrane interface. The pH (low) insertion peptide (pHLIP) is a peptide that inserts across a membrane bilayer depending on the pH due to the presence of a key residue (Asp14) whose acidity-induced protonation triggers the whole process. The complex nature of these peptide/membrane interactions resulted in sampling limitations of the protonation and configurational space albeit using state-of-the-art methods such as the constant-pH molecular dynamics. To address this issue and circumvent those limitations, new simulations were performed with our newly developed pH-replica exchange method using wild-type (wt)-pHLIP in different 2-oleoyl-1-palmitoyl-sn-glycero-3-phosphocholine membrane sizes. This technique provided enhanced sampling and allowed for the calculation of more complete Asp14 pK_a profiles. The conformational heterogeneity derived from strong electrostatic interactions between Asp14 and the lipid phosphate groups was identified as the source of most pK_a variability. In spite of these persistent and harder-to-equilibrate phosphate interactions, the pK_a values at deeper regions (6.0-6.2) still predicted the experimental pK of insertion (6.0) since the electrostatic perturbation decays as the residue inserts further into the membrane. We also observed that reducing the system size leads to membrane deformations where it increasingly loses the ability to accommodate the pHLIP-induced perturbations. This indicates that large membrane patches, such as 256 or even 352 lipids, are needed to obtain stable and more realistic pHLIP/membrane systems. These results strengthen our method pK_a predictive and analytical capabilities to study the intricate play of electrostatic effects of the peptide/membrane interface, granting confidence for future applications in similar systems.

In silico structural elucidation of the rabies RNA-dependent RNA polymerase (RdRp) toward the identification of potential rabies virus inhibitors

The rabies virus (RABV) is a non-segmented, negative single-stranded RNA virus which causes acute infection of the central nervous system in humans. Once symptoms appear, the result is nearly always death, and to date, post-exposure prophylaxis (PEP) is the only treatment applicable only immediately after an exposure. Previous studies have identified viral RNA-dependent RNA polymerase (RdRp) as a potential drug target due to its significant role in viral replication and transcription. Herein we generated an energy-minimized homology model of RABIES-RdRp and used it for virtual screening against 2045 NCI Diversity Set III library. The best five ligand-RdRp complexes were picked for further energy minimization via molecular dynamics (MDs) where the complex with ligand Z01690699 shows a minimum score characterized with stable hydrogen bonds and hydrophobic interactions with the catalytic site residues. Our study identified an important ligand for development of remedial approach for treatment of rabies infection.

On the Effect of the Various Assumptions and Approximations used in Molecular Simulations on the Properties of Bio-Molecular Systems: Overview and Perspective on Issues

Computer simulations of molecular systems enable structure-energy-function relationships of molecular processes to be described at the sub-atomic, atomic, supra-atomic or supra-molecular level and plays an increasingly important role in chemistry, biology and physics. To interpret the results of such simulations appropriately, the degree of uncertainty and potential errors affecting the calculated properties must be considered. Uncertainty and errors arise from (1) assumptions underlying the molecular model, force field and simulation algorithms, (2) approximations implicit in the interatomic interaction function (force field), or when integrating the equations of motion, (3) the chosen values of the parameters that determine the accuracy of the approximations used, and (4) the nature of the system and the property of interest. In this overview, advantages and shortcomings of assumptions and approximations commonly used when simulating bio-molecular systems are considered. What the developers of bio-molecular force fields and simulation software can do to facilitate and broaden research involving bio-molecular simulations is also discussed.

Liposomes embedded in layer by layer constructs as simplistic extracellular vesicles transfer model

Extracellular vesicles (EVs) are particles originating from the exfoliation of the cellular membrane. They are involved in cell-to-cell and cell-to-matrix signaling, exchange of bioactive molecules, tumorigenesis and metastasis, among others. To mitigate the limited understanding of EVs transfer phenomena, we developed a simplistic model that mimics EVs and their interactions with cells and the extracellular matrix. The proposed model is a layer by layer (LbL) film built from the polycationic poly-l-lysine (PLL) and the glycosaminoglycan hyaluronic acid (HA) to provide ECM mimicry. Positively charged 1,2-dipalmitoyl-sn-glycero-3-phosphocholine (DPPC) and N¹,N¹,N¹⁴,N¹⁴-tetramethyl-N¹,N¹⁴-ditetradecyltetradecane-1,14-diaminium dibromide (GS14) liposomes were embedded in this construct to act as EVs analogs. To simulate EVs carrying substances, Nile Red was loaded as a model of lipophilic cargo molecules. The integration of each component was followed by quartz crystal microbalance measurements, which confirmed the immobilization of intact liposomes on the underlying (PLL/HA)₃ soft film. The release of Nile Red from liposomes either embedded in the LbL construct or exposed at its surface revealed a fast first order release. This system was validated as a model for EV/cell interactions by incubation with breast cancer cells MDA-MB-231. We observed higher internalization for embedded liposomes when compared with surface-exposed ones, showcasing that the ECM mimic layers do not constitute a barrier to liposome/cell interactions but favor them.

The effect of different cutoff schemes in molecular simulations of proteins

Molecular simulations of nanoscale systems invariably involve assumptions and approximations to describe the electrostatic interactions, which are long-ranged in nature. One approach is the use of cutoff schemes with a reaction-field contribution to account for the medium outside the cutoff scheme. Recent reports show that macroscopic properties may depend on the exact choice of cutoff schemes in modern day simulations. In this work, a systematic analysis of the effects of different cutoff schemes was performed using a set of 52 proteins. We find no statistically significant differences between using a twin-range or a single-range cutoff scheme. Applying the cutoff based on charge groups or based on atomic positions, does lead to significant differences, which is traced to the cutoff noise for energies and forces. While group-based cutoff schemes show increased cutoff noise in the potential energy, applying an atomistic cutoff leads to artificial structure in the solvent at the cutoff distance. Carefully setting the temperature control, or using an atomistic cutoff for the solute and a group-based cutoff for the solvent significantly reduces the effects of the cutoff noise, without introducing structure in the solvent. This study aims to deepen the understanding of the implications different cutoffs have on molecular dynamics simulations.

Improved GROMOS 54A7 Charge Sets for Phosphorylated Tyr, Ser, and Thr to Deal with pH-Dependent Binding Phenomena

Phosphorylation is a ubiquitous post-translational modification in proteins, and the phosphate group is present constitutively or transiently in most biological building blocks. These phosphorylated biomolecules are involved in many high-affinity binding/unbinding events that rely predominantly on electrostatic interactions. To build accurate models of these molecules, we need an improved description of the atomic partial charges for all relevant protonation states. In this work, we showed that the commonly used protocols to derive atomic partial charges using well-solvated molecules are inadequate to model the protonation equilibria in binding events. We introduced a protocol based on PB/MC calculations with a single representative conformation (of both protonation states) and used the resulting pK_a estimations to help manually curate the atomic partial charges. The final charge set, which is fully compatible with the GROMOS 54A7 force field, proved to be very effective in modeling the protonation equilibrium in different phosphorylated peptides in the free (tetrapeptides, pentapeptides, and pY1021) and protein-complexed forms (pY1021/PLC-γ1 complex). This was particularly important in the case of the pY1021 bound to the SH2 domain of PLC-γ1, where only our curated charge set captured the correct protonation equilibrium at the neutral to slightly acidic pH range. The binding/unbinding phenomena in that pH range are biologically relevant, and to improve our models, we need to go beyond the commonly used protocols and obtain revised force field parameters for these molecules.

The Effect of Using a Twin-Range Cutoff Scheme for Nonbonded Interactions: Implications for Force-Field Parametrization?

Recently, concerns have been voiced regarding the validity of the GROMOS force fields, being parametrized using a twin-range cutoff scheme, in which longer ranged nonbonded forces and energies are updated less frequently than shorter ranged ones. Here we demonstrate that the influence of such a scheme on the thermodynamic, structural, and dynamic properties used in the parametrization of the GROMOS force fields is minor. We find root-mean-square differences of maximally 0.5 kJ/mol for the solvation free energy and heat of vaporization and of maximally 0.4% for the density. Slightly larger differences are observed when switching from a group-based to an atom-based cutoff scheme. In cases where the twin-range cutoff scheme does result in minor differences compared to a single-range cutoff these are well within the deviation from the experimentally measured values.

Reaction-field electrostatics in molecular dynamics simulations: development of a conservative scheme compatible with an atomic cutoff

Shifting and switching schemes are developed to enable strict energy conservation in molecular dynamics simulations relying on reaction-field electrostatic (as well as Lennard-Jones) interactions with an atom-based cutoff truncation.

Atomic Partitioning of the MPn (n = 2, 3, 4) Dynamic Electron Correlation Energy by the Interacting Quantum Atoms Method: A Fast and Accurate Electrostatic Potential Integral Approach

Recently, the quantum topological energy partitioning method called interacting quantum atoms (IQA) has been extended to MPn (n = 2, 3, 4) wave functions. This enables the extraction of chemical insight related to dynamic electron correlation. The large computational expense of the IQA-MPn approach is compensated by the advantages that IQA offers compared to older nontopological energy decomposition schemes. This expense is problematic in the construction of a machine learning training set to create kriging models for topological atoms. However, the algorithm presented here markedly accelerates the calculation of atomically partitioned electron correlation energies. Then again, the algorithm cannot calculate pairwise interatomic energies because it applies analytical integrals over whole space (rather than over atomic volumes). However, these pairwise energies are not needed in the quantum topological force field FFLUX, which only uses the energy of an atom interacting with all remaining atoms of the system that it is part of. Thus, it is now feasible to generate accurate and sizeable training sets at MPn level of theory. © 2019 The Authors. Journal of Computational Chemistry published by Wiley Periodicals, Inc.

Toward realistic computer modeling of paraffin-based composite materials: critical assessment of atomic-scale models of paraffins

Paraffin-based composites represent a promising class of materials with numerous practical applications such as e.g. heat storage. Computer modeling of these complex multicomponent systems requires a proper theoretical description of both the n-alkane matrix and the non-alkane filler molecules. The latter can be modeled with the use of a state-of-the-art general-purpose force field such as GAFF, CHARMM, OPLS-AA and GROMOS, while the paraffin matrix is traditionally described in the frame of relatively old, alkane-specific force fields (TraPPE, NERD, and PYS). In this paper we link these two types of models and evaluate the performance of several general-purpose force fields in computer modeling of paraffin by their systematic comparison with earlier alkane-specific models as well as with experimental data. To this end, we have performed molecular dynamics simulations of n-eicosane bulk samples with the use of 10 different force fields: TraPPE, NERD, PYS, OPLS-UA, GROMOS, GAFF, GAFF2, OPLS-AA, L-OPLS-AA, and CHARMM36. For each force field we calculated several thermal, structural and dynamic characteristics of n-eicosane over a wide temperature range. Overall, our findings show that the general-purpose force fields such as CHARMM36, L-OPLS-AA and GAFF/GAFF2 are able to provide a realistic description of n-eicosane samples. While alkane-specific models outperform most general-purpose force fields as far as the temperature dependence of mass density, the coefficient of volumetric thermal expansion in the liquid state, and the crystallization temperature are concerned, L-OPLS-AA, CHARMM36 and GAFF2 force fields provide a better match with experiment for the shear viscosity and the diffusion coefficient in melt. Furthermore, we show that most general-purpose force fields are able to reproduce qualitatively the experimental triclinic crystal structure of n-eicosane at low temperatures.

Atomic-scale computational models of paraffins are critically assessed and compared.