Effects of bundling on the properties of the SPC water model

Benchmarking a dual-scale hybrid simulation framework for small globular proteins combining the CHARMM36 and Martini2 models

Multi-scale models in which varying resolutions are considered in a single molecular dynamics simulation setup are gaining importance in integrative modeling. However, combining atomistic and coarse-grain resolutions, especially for coarse-grain force fields derived from top-down approaches, have not been well explored. In this study, we have implemented and tested a dual-resolution simulation approach to model globular proteins in atomistic detail (represented by the CHARMM36 model) with the surrounding solvent in Martini2 coarse-grain detail. The hybrid scheme considered is an extension of a model implemented earlier for mainly lipid and water molecules. We have considered a set of small globular proteins and have extensively compared to atomistic benchmark simulations as well as a host of experimental observables. We show that the protein structural dynamics sampled in the hybrid scheme is robust, and the intra-protein contact maps are reproduced, despite increased fluctuations of the loop regions. A good match is observed with experimental small angle X-ray scattering (SAXS) and NMR observables, such as chemical shifts and [Formula: see text] -coupling, with the best match obtained for the chemical shifts. However, deviations are observed in the water dynamics and protein-water interactions which we attribute to the limitation of solvent screening in the coarse-grain force field. The computational speed-up achieved is about 2-3 times compared to an all-atom system. Overall, the hybrid model is able to retain the main features of the underlying atomistic conformational landscape with a two-fold speed-up in computational cost.

A potential therapeutic strategy by fungal laccase targeting novel binding sites on human cytomegalovirus DNA polymerase

Human cytomegalovirus (HCMV) is a common herpesvirus that can severely affect transplant recipients, those with AIDS, and newborns. Existing synthetic medications face limitations, including toxicity, processing issues, and viral resistance. As part of this study, the efficacy of the extracellular enzyme laccase isolated from a widely available mushroom (Pleurotus pulmonarius) was compared to that of ganciclovir, a common antiviral, used against HCMV. The study found that laccase can synergistically inhibit HCMV replication by targeting new inhibitory sites on the UL54 protein. Viral replication requires significant energy, increasing cellular respiration. The antiviral effect of laccase was linked to reduced expression of genes regulating cellular respiration, which coincided with decreased viral DNA copies. Additionally, in silico analysis has identified a novel binding site for the laccase enzyme in the C-terminal region of HCMV DNA polymerase specifically between amino acids 1004 and 1242, which effectively obstructs the binding of the essential viral replication regulatory accessory protein UL44, thereby hindering successful replication. Molecular dynamics simulations were performed under standardized conditions mimicking a cellular environment, revealing a stable protein-protein docking complex. This study may aid in developing novel antiviral strategies by utilizing laccase's target specificity to regulate host cellular pathways against Herpesviridae.

Hydrodynamics and Aggregation of Nanoparticles with Protein Corona: Effects of Protein Concentration and Ionic Strength

Multiple 10 nm-sized anionic nanoparticles complexed with plasma proteins (human serum albumin (SA) or immunoglobulin gamma-1 (IgG)) at different ratios are simulated using all-atom and coarse-grained models. Coarse-grained simulations show much larger hydrodynamic radii of individual particles at a low protein concentration (a protein-to-particle ratio of 1) than at high protein concentrations or without proteins, indicating particle aggregation only at such a low protein concentration, in agreement with experiments. This particle aggregation is attributed to both electrostatic and hydrophobic particle-protein interactions, to an extent dependent on different proteins. In all-atom simulations, IgG proteins induce particle aggregation with and without salt, while SA proteins promote particle aggregation only in the presence of salt that can weaken the electrostatic repulsion between anionic particles closely linked via SA that is smaller than IgG, which also agree well with experiments. Besides charge interactions, hydrophobic interactions between particles and proteins are also important especially at the high salt concentration, leading to the increased particle-protein contact area. These findings help explain experimental observations regarding that the effects of protein concentration and ionic strength on particle aggregation depend on different plasma proteins, which are interpreted by binding free energies, electrostatic, and hydrophobic interactions between particles and proteins.

Identification of novel PAD2 inhibitors using pharmacophore-based virtual screening, molecular docking, and MD simulation studies

In the realm of epigenetic regulation, Protein arginine deiminase 2 (PAD2) stands out as a therapeutic target due to its significant role in neurological disorders, rheumatoid arthritis (RA), multiple sclerosis (MS), and various cancers. To date, no in silico studies have focused on PAD2 for lead compound identification. Therefore, we conducted structure-based pharmacophore modeling, virtual screening, molecular docking, molecular dynamics (MD) simulations, and essential dynamics studies using PCA and free energy landscape analyses to identify repurposed drugs and selective inhibitors against PAD2. The best pharmacophore model, 'Pharm_01,' had a selectivity score of 10.485 and an excellent ROC curve quality of 0.972. Pharm1 consisted of three hydrogen bond donors (HBD) and two hydrophobic (Hy) features (DDDHH). A virtual screening of about 9.2 million compounds yielded 2575 hits using a fit value threshold of 2.5 and drug-likeness criteria. Molecular docking identified the top ten molecules, which were verified using MD simulations. Stability was verified using MM-PBSA studies, whereas conformational differences were investigated using PCA and free energy landscape analyses. Two hits (Leads 1 and 2) from the DrugBank dataset showed promise for repurposing as PAD2 inhibitors, while one hit compound (Lead 8) from the ZINC database emerged as a novel PAD2 inhibitor. These findings indicate that the discovered compounds may be potent PAD2 inhibitors, necessitating additional preclinical and clinical research to produce viable treatments for cancer and neurological disorders.

Discerning potent CSF-1r inhibitors for targeting and therapy of neuroinflammation using computational approaches

Microglia, the primary cellular mediator of neuroinflammation, plays a pivotal role in numerous neurological disorders. Precise and non-invasive quantification of microglia is of paramount importance. Despite various investigations into cell-specific biomarkers for assessing neuroinflammation, many suffer from poor cellular specificity and low signal-to-noise ratios. Colony-stimulating factor-1 receptor (CSF-1R), also known as FMS kinase, has emerged as a promising neuroinflammation biomarker with significant relevance to inflammatory diseases. Additionally, CSF-1R inhibitors (CSF-1Ri) have shown therapeutic potential in central nervous system (CNS) pathological conditions by depleting microglia. Therefore, the development of more specific CSF-1R inhibitors for targeting and treating various CNS insults and neurological disorders is imperative. This study focuses on the search for novel CSF-1R inhibitors. Based on the literature on CSF-1R inhibitors, we proposed and investigated ten ligands as novel CSF-1R inhibitors. Among these, the top three ligands, selected based on their maximum binding scores in docking calculations, are subjected to 100 nanoseconds of molecular dynamics (MD) simulation, alongside three reference ligands. All protein-ligand complexes remain stable throughout the dynamics and exhibit minimal fluctuations during the analysis. The results obtained through this study may prove significant for the future design of CSF-1R inhibitors with potential applications in the field of biomedicine.

Molecular insights from structural dynamics of HER2-inhibitor complexes pave the way for new breast cancer drugs

The human epidermal growth factor receptor 2 (HER2) is closely associated with the development and progression of breast cancer, making it a critical target for therapeutic interventions. In this study, we employed a comprehensive computational drug discovery strategy to identify potential inhibitors of HER2. Our approach combined virtual screening, re-docking procedures, molecular dynamics (MD) simulations, and free energy landscape analysis using principal component analysis (PCA). From the extensive PubChem library, we initially screened 733 compounds for their binding potential to HER2, using docking scores as a primary filter. These scores ranged notably from -11.172 to -7.028 kcal/mol, indicating substantial binding capacities. Following this screening, we selected four promising compounds (PubChem CID 166029206, 166544027, 21031510, and 11712721) along with a control compound (70I) for in-depth analysis. Utilizing the Amber software suite for MD simulations, we conducted 200-nanosecond simulations to assess the interactions and binding efficiencies of these selected compounds with HER2. We analysed the molecular interactions through various parameters such as root mean square deviation (RMSD), root mean square fluctuation (RMSF), and hydrogen bond formation patterns, free binding energy calculations. The PCA-based free energy landscape analysis revealed that these compounds consistently occupied a distinct low-energy basin, indicating their high stability and strong binding affinity for the HER2. This detailed analysis provided insights into the stability and conformational dynamics of these potential inhibitors when bound to the HER2. Our findings pave the way for further experimental validation and development of these compounds as therapeutic agents in breast cancer treatment.

Investigating the applicability of novel hydrate dissociation inhibitors in oilwell cement through molecular simulations

In the field of hydrate formation cementing, the method of developing the low hydration exothermic cement systems cannot effectively solve the problem of hydrate dissociation caused by the hydration heat release of cement. Therefore, we proposed a new approach to address this issue by employing cement additives that can effectively delay the dissociation of hydrate. In our previous work, we designed a novel hydrate dissociation inhibitor, PVCap/dmapma, however, its applicability with cement slurry remains unverified. In this study, we established a more realistic model of oilwell cement gel based on experimental data. Additionally, we investigated the potential effects of PVCap/dmapma on the microstructure and mechanical properties of cement gel through molecular simulations. The results suggest that PVCap/dmapma has no negative effect on the performance of cement slurry compared to Lecithin. By adding PVCap/dmapma to cement slurry, the problem of cementing in hydrate formations is expected to be solved.

Sequence Sensitivity in Membrane Remodeling by Polyampholyte Condensates

Intrinsically disordered peptides (IDPs) have been found to undergo liquid-liquid phase separation (LLPS) and produce complex coacervates that play numerous regulatory roles in the cell. Recent experimental studies have discovered that LLPS at or near the membrane surface helps in the biomolecular organization during signaling events and can significantly alter the membrane morphology. However, the molecular mechanism and microscopic details of such processes still remain unclear. Here we study the effect of polyampholyte and polyelectrolyte condensation on two different anionic membranes, as they represent a majority of naturally occurring IDPs. The polyampholytes are fifty-residue polymers, made of glutamate(E) and lysine(K) with different charge patterns. The polyelectrolytes are separate chains of E25 and K25. We first calibrate the MARTINI v3.0 force field and then perform long-time-scale coarse-grained molecular dynamics simulations. We find that condensates formed by all the polyampholytes get adsorbed on the membrane. However, the strong polyampholytes (i.e., blocky sequences) can remodel the membranes more prominently than the weaker ones (i.e., scrambled sequences). Condensates formed by the blocky sequences induce a significant negative curvature (∼0.1 nm-1) and local demixing of lipids, whereas those by the scrambled sequences tend to wet the membrane to a greater extent without generating significant curvature or demixing. We perform several microscopic analyses to characterize the nature of the interaction between membranes and these condensates. Our analyses of interaction energetics reveal that membrane remodeling and/or wetting are favored by enhanced interactions between polyampholytes with lipids and the counterions.

Cheminformatics approach for identification of N-HyMenatPimeMelly as a novel potential ligand against RAS and renal chloride channel

Some angiotensin receptor (AR) blockers interfere with the renal chloride channel (ClC-K), which plays an important role in urine concentration. Identifying ligands targeting this channel, whether activating or blocking, is highly desirable because it could open the way for interventions that modulate their activity. In this study, the Asinex (BioDesign) complete library was screened to identify a compound with favorable physicochemical and pharmacokinetic properties, which have both AR blocking and ClC-Ka-modulating activities to present it as a novel potential oral candidate which could be useful for treatment of salt-sensitive hypertension without major ClC-K affection. A compound, N-{[4-Hydroxy-1-(2-methyl-1,6-naphthyridin-4-yl)-4-piperidinyl]methyl}-N-methyl-L-lysinamide (N-HyMenatPimeMelly) (Chem Spider ID 68416221), was identified as a potent potential oral ligand of the renin-angiotensin system (RAS) and ClC-Ka with docking scores ranging from -10.978 to -7.324 with the four selected proteins (4YAY: AR type 1, 2PFI: Cytoplasmic domain of ClC-Ka, 6JOD: AR type 2 and 6M0J: Angiotensin-converting enzyme 2). The protein-ligand complex was used to perform molecular dynamics (MD) simulation for 100 ns. The QikProp and SwissADME tools' results showed that the compound has ADME/T and drug-likeness properties, which are within the permissible ranges for 95% of known drugs. The density functional theory (DFT) analysis and MD simulation extended the study toward computational validation. Throughout the study, N-HyMenatPimeMelly has shown good interactions and stable performance in MD simulation and DFT analysis. The whole analysis has produced promising results, and N-HyMenatPimeMelly can be treated as a novel potential RAS and ClC-K oral ligand, however, experimental validation is needed before human use.Communicated by Ramaswamy H. Sarma.

Permeability of antioxidants through a lipid bilayer model with coarse-grained simulations

Oxidative stress caused by pollution and lifestyle changes causes an excess of free radicals that react chemically with cell constituents leading to irreversible damage. There are molecules known as antioxidants that reduce the levels of free radicals. Some pigments of fruits and vegetables known as anthocyanins have antioxidant properties. Their interaction with the cell membrane becomes a crucial step in studying these substances. In this research, molecular dynamics simulations, particularly, coarse-grained molecular dynamics (CGMD) were used. This technique aims to replace functional groups with corresponding beads that represent their level of polarity and affinities to other chemical groups. Also, umbrella sampling was carried out to obtain free energy profiles that describe well the orientation and location of antioxidants in a membrane considering Trolox, Cyanidin, Gallic Acid, and Resveratrol molecules to study the structural effects they cause on it. It was concluded in this study that an antioxidant when crossing the membrane does not cause either damage to the structural properties or the loss of packing and stratification of phospholipids. it was also observed that the most reactive part of the molecules could easily approach area A prone to lipid oxidation, which can describe the antioxidant capacity of these molecules.Communicated by Ramaswamy H. Sarma.

In silico investigation on the mutational analysis of BRCA1-BARD1 RING domains and its effect on nucleosome recognition and ubiquitination

The BRCA1-BARD1 complex is a crucial tumor suppressor E3 ubiquitin ligase involved in DNA double-stranded break repair. The BRCA1-BARD1 RING domains interact with UBE2D3 through the BRCA1 interface and this complex flexibly tether to the nucleosome core particle (NCP), where BRCA1 and BARD1 interacts with histone H2A and H2B of NCP. Mutations in the BRCA1-BARD1 RING domains have been linked to familial breast and ovarian cancer. Seven mutations were analyzed to understand their effect on the binding interface of protein partners and changes in conformational dynamics. Molecular dynamics simulations revealed that mutant complexes were less conformationally flexible than the wildtype complex. Protein-protein interaction profiling showed the importance of specific molecular interactions, hotspot and hub residues, and some of these were lost in the mutant complexes. Two mutations (BRCA1L51W-K65R and BARD1C53W) hindered significant interaction between protein partners and may prevent signaling for ubiquitination of histones in NCP and other cellular targets. The structural compactness and reduced significant interaction in mutant complexes may be the possible reason of preventing ubiquitination and hinder DNA repair, resulting cancer.

In-silico studies on wild orange (Citrus macroptera Mont.) compounds against COVID-19 pro-inflammation targets

One-fifth of COVID-19 patients suffer a severe course of COVID-19 (SARS-CoV-2) infection; however, the specific causes remain unclear. Despite numerous papers that have been flooded in different scientific journals clear clinical picture of COVID-19 aftermath persists to remain fuzzy. The survivors of severe COVID-19infection having defeated the virus are just the starting of an uncharted recovery path. Currently, there is no drug available that is safe to consume to combat this pandemic. However, researchers still struggling to find specific therapeutic solutions. The present study employed an in silico approach to assessing the inhibitory potential of the phytochemicals obtained from GC-MS analysis of Citrus macroptera against inflammatory proteins like COX-2, NMDAR and VCAM-1 which remains in a hyperactive state even after a patient is fully cured of this deadly mRNA virus. An extensive molecular docking investigation of the phyto-compounds at the active binding pockets of the inflammatory proteins revealed the promising inhibitory potential of the phytochemicals. Reasonable physicochemical attributes of the compounds following Lipinski's rule of five, VEBER and PAINS analysis further established them as potential therapeutic candidates against aforesaid inflammatory proteins. MM-GBSA binding free energy estimation revealed that Limonene was the most promising candidate displaying the highest binding efficacy with the concerned VCAM-1 protein included in the present analysis. An interesting finding is the phytochemicals exhibited better binding energy scores with the concerned COX-2, VCAM-1 and NMDA receptor proteins than the conventional drugs that are specifically targeted against them. Our in silico results suggest that all the natural phyto-compounds derived from C. macroptera could be employed in Post covid inflammation complexities after appropriate pre-clinical and clinical trials for further scientific validation.Communicated by Ramaswamy H. Sarma.

DFT Calculation and MD Simulation Studies on Gemini Surfactant Corrosion Inhibitor in Acetic Acid Media

Gemini surfactant corrosion inhibitor (CI) is one type of CI mainly used in mitigating corrosion in the complex system of oil/gas production industries. Computer modeling methods such as density functional theory (DFT) calculation and molecular dynamic (MD) simulation are required to develop new CI molecules focusing on their application condition as a prediction or screening process before the physical empirical assessment. In this work, the adsorption inhibition efficiencies of two monomer surfactants (2B and H) and their respective Gemini structures with the addition of different spacers (alkyl, benzene, ester, ether, and ketone) are investigated using DFT calculation and MD simulation method in 3% sodium chloride (NaCl), and 1500 ppm acetic acid solutions. In DFT calculation, 2B-benzene molecules are assumed to have the most promising inhibition efficiency based on their high reactivity and electron-donating ability at their electron-rich benzene ring region based on the lowest bandgap energy (0.765 eV) and highest HOMO energy value (-2.879 eV), respectively. DFT calculation results correlate with the adsorption energy calculated from MD simulation, where 2B-benzene is also assumed to work better as a CI molecule with the most adsorption strength towards Fe (110) metal with the highest negative adsorption energy value (-1837.33 kJ/mol at temperature 323 K). Further, diffusion coefficient and molecular aggregation analysis in different CI concentrations through MD simulation reveals that only a small amount of Gemini surfactant CI is needed in the inhibition application compared to its respective monomer. Computer simulation methods successfully predict and screen the Gemini surfactant CI molecules that can work better as a corrosion inhibitor in acetic acid media. The amount of Gemini surfactant CI that needs to be used is also predicted. The future planning or way forward from this study will be the development of the most promising Gemini surfactant CI based on the results from DFT calculation and MD simulations.

The thermodynamics of enhanced dope stability of cellulose solution in NaOH solution by urea

The addition of urea in pre-cooled alkali aqueous solution is known to improve the dope stability of cellulose solution. However, its thermodynamic mechanism at a molecular level is not fully understood yet. By using molecular dynamics simulation of an aqueous NaOH/urea/cellulose system using an empirical force field, we found that urea was concentrated in the first solvation shell of the cellulose chain stabilized mainly by dispersion interaction. When adding a glucan chain into the solution, the total solvent entropy reduction is smaller if urea is present. Each urea molecule expelled an average of 2.3 water molecules away from the cellulose surface, releasing water entropy that over-compensates the entropy loss of urea and thus maximizing the total entropy. Scaling the Lennard-Jones parameter and atomistic partial charge of urea revealed that direct urea/cellulose interaction was also driven by dispersion energy. The mixing of urea solution and cellulose solution in the presence or absence of NaOH are both exothermic even after correcting for the contribution from dilution.

8-Amide and 8-carbamate substitution patterns as modulators of 7-hydroxy-4-methylcoumarin's antidepressant profile: Synthesis, biological evaluation and docking studies

Psychiatric and neurological disorders affect millions of people worldwide. Currently available treatments may help to improve symptoms, but they cannot cure the diseases. Therefore, there is an urgent need for potent and safe therapeutic solutions. 8-Amide and 8-carbamatecoumarins were synthetized and evaluated as human monoamine oxidase A and B (hMAO-A and hMAO-B) inhibitors. Comparison between both scaffolds has been established, and we hypothesized that the introduction of different substituents can modulate hMAO activity and selectivity. N-(7-Hydroxy-4-methylcoumarin-8-yl)-4-methylbenzamide (9) and ethyl N-(7-hydroxy-4-methylcoumarin-8-yl)carbamate (20) proved to be the most active and selective hMAO-A inhibitors (IC₅₀ = 15.0 nM and IC₅₀ = 22.0 nM, respectively), being compound 9 an irreversible hMAO-A inhibitor twenty-four times more active in vitro than moclobemide, a drug used in the treatment of depression and anxiety. Based on PAMPA assay results, both compounds proved to be good candidates to cross the blood-brain barrier. In addition, these compounds showed non-significant cytotoxicity on neuronal viability assays. Also, the best compound proved to have a t_1/2 of 6.84 min, an intrinsic clearance of 195.63 μL min^-1 mg^-1 protein, and to be chemically stable at pH 3.0, 7.4 and 10.0. Docking studies were performed to better understand the binding affinities and selectivity profiles for both hMAO isoforms. Finally, theoretical drug-like properties calculations corroborate the potential of both scaffolds on the search for new therapeutic solutions for psychiatric disorders as depression.

Molecular dynamics simulations reveal the effect of mutations in the RING domains of BRCA1-BARD1 complex and its relevance to the prognosis of breast cancer

The N-terminal RING-RING domain of BRCA1-BARD1 is an E3 ubiquitin ligase complex that plays a critical role in tumor suppression through DNA double stranded repair mechanism. Mutations in the BRCA1-BARD1 heterodimer RING domains were found to have an association with breast and ovarian cancer by a way of hampering the E3 ubiquitin ligase activity. Herein, the molecular mechanism of interaction, conformational change due to the specific mutations on the BRCA1-BARD1 complex at atomic level has been examined by employing molecular modeling techniques. Sixteen mutations have been selected for the study. Molecular dynamics simulation results reveal that the mutant complexes have more local perturbation with a high residual fluctuation in the zinc binding sites and central helix. A few of the BRCA1 (V11A, I21V, I42V, R71G, I31M and L51W) mutants have been experimentally identified that do not impair E3 ligase activity, display an enhanced number of H-bonds and non-bonded contacts at the interacting interface as revealed by MD simulation. The mutation of BRCA1 (C61G, C64Y, C39Y and C24R) and BARD1 (C53W, C71Y and C83R) zinc binding residues displayed a smaller number of significant H-bonds, other interactions and also loss of some of the hotspot residues. Additionally, most of the mutant complexes display relatively lower electrostatic energy, H-bonding and total stabilizing energy as compared to wild-type. The current study attempts to unravel the role of BRCA1-BARD1 mutations and delineates the structural and conformational dynamics in the progression of breast cancer.Communicated by Ramaswamy H. Sarma.

Molecular docking analysis of mefluhybenamine with lung cancer targets

Lung cancer is the most prevalent type of cancer worldwide, with 2.21 million cases and 1.80 million fatalities in 2020. The main factor influencing lung cancer is smoking, and the most common form of lung cancer, non-small cell lung cancer (NSCLC), accounts for around 80% of instances compared to small cell carcinoma, and about 75% of patients are already in an advanced stage when they are detected. Despite significant early detection and therapy improvements, the five-year survival rate for NSCLC is not encouraging. Therefore, it is essential to look into the molecular origins of non-small cell lung cancer to develop more effective therapeutic strategies-the binding affinities and energy landscape with the proteins. Cyclin Dependent kinase 2 (CDK2) and Insulin-like Growth Factor 1 Receptor (IGF1) were more substantial and sustained in lung cancer that was chosen as the two primary target proteins in this. We screened the entire Drug Bank-prepared library of 1,55,888 compounds and found (2R,3R)-7-(Methylsulfonyl)-3-(2,4,5-trifluorophenyl) -1,2,3,4-tetrahydropyrido[1,2-a] benzimidazol-2-aminium (Mefluhybenamine) to be a significant inhibitor. Mefluhybenamine showed strong hydrogen bonding and other bonding topologies, such as van der Waals force, in its high docking scores of -6.168 Kcal/mol and -5.26 Kcal/mol, and ADMET results showed excellent bioavailability, remarkable solubility, no side effects, and toxicity. The molecular dynamicsimulation confirmed the compound's stability and interaction pattern for 100 ns in an SPC water medium with the slightest deviation and fluctuation. Data shows that Mefluhybenamine is a potential candidate. However, validation of the compound is essential.

The Performance of Different Water Models on the Structure and Function of Cytochrome P450 Enzymes

Modeling approaches and modern simulations to investigate the biomolecular structure and function rely on various methods. Since water molecules play a crucial role in all sorts of chemistry, the accurate modeling of water molecules is vital for such simulations. In cytochrome P450 (CYP450), in particular, water molecules play a key role in forming active oxidant that ultimately performs oxidation and metabolism. In the present study, we have highlighted the behavior of the three most widely used water models─TIP3P, SPC/E, and OPC─for three different CYP450 enzymes─CYP450_BM3, CYP450_OleT, and CYP450_BSβ─during MD simulations and QM/MM calculations. We studied the various properties, such as RMSD, RMSF, H-bond, water occupancy, and hydrogen atom transfer (HAT), using QM/MM calculations and compared them for all three water models. Our study shows that the stabilities of the enzyme complexes are well maintained in all three water models. However, the OPC water model performs well for the polar active sites, that is, in CYP450_OleT and CYP450_BSβ, while the TIP3P water model is superior for the hydrophobic site, such as CYP450_BM3.

A Computational Study on the Interaction of NSP10 and NSP14: Unraveling the RNA Synthesis Proofreading Mechanism in SARS-CoV-2, SARS-CoV, and MERS-CoV

The interaction of exoribonuclease (ExoN) nonstructural protein (NSP14) with NSP10 co-factors is crucial for high-fidelity proofreading activity of coronavirus replication and transcription. Proofreading function is critical for maintaining the large genomes to ensure replication proficiency; therefore, while maintaining the viral replication fitness, quick resistance has been reported to the nucleotide analogue (NA) drugs. Therefore, targeting the NSP14 and NSP10 interacting interface with small molecules or peptides could be a better strategy to obstruct replication processes of coronaviruses (CoVs). A comparative study on the binding mechanism of NSP10 with the NSP14 ExoN domain of SARS-CoV-2, SARS-CoV, MERS-CoV, and four SARS-CoV-2 NSP14mutant complexes has been carried out. Protein-protein interaction (PPI) dynamics, per-residue binding free energy (BFE) analyses, and the identification of interface hotspot residues have been studied using molecular dynamics simulations and various computational tools. The BFE of the SARS-CoV NSP14-NSP10 complex was higher when compared to novel SARS-CoV-2 and MERS. However, SARS-CoV-2 NSP14mutant systems display a higher BFE as compared to the wild type (WT) but lower than SARS-CoV and MERS. Despite the high BFE, the SARS-CoV NSP14-NSP10 complex appears to be structurally more flexible in many regions especially the catalytic site, which is not seen in SARS-CoV-2 and its mutant or MERS complexes. The significantly high residue energy contribution of key interface residues and hotspots reveals that the high binding energy between NSP14 and NSP10 may enhance the functional activity of the proofreading complex, as the NSP10-NSP14 interaction is essential in maintaining the stability of the ExoN domain for the replicative fitness of CoVs. The factors discussed for SARS-CoV-2 complexes may be responsible for NSP14 ExoN having a high replication proficiency, significantly leading to the evolution of new variants of SARS-CoV-2. The NSP14 residues V66, T69, D126, and I201and eight residues of NSP10 (L16, F19, V21, V42, M44, H80, K93, and F96) are identified as common hotspots. Overall, the interface area, hotspot locations, bonded/nonbonded contacts, and energies between NSP14 and NSP10 may pave a way in designing potential inhibitors to disrupt NSP14-NSP10 interactions of CoVs especially SARS-CoV-2.

Using Atomistic Simulations to Explore the Role of Methylation and ATP in Chemotaxis Signal Transduction

A bacterial chemotaxis mechanism is activated when nutrients bind to surface receptors. The sequence of intra- and interprotein events in this signal cascade from the receptors to the eventual molecular motors has been clearly identified. However, the atomistic details remain elusive, as in general may be expected of intraprotein signal transduction pathways, especially when fibrillar proteins are involved. We performed atomistic calculations of the methyl accepting chemoprotein (MCP)-CheA-CheW multidomain complex from Escherichia coli, simulating the methylated and unmethylated conditions in the chemoreceptors and the ATP-bound and apo conditions of the CheA. Our results indicate that these atomistic simulations, especially with one of the two force fields we tried, capture several relevant features of the downstream effects, such as the methylation favoring an intermediate structure that is more toward a dipped state and increases the chance of ATP hydrolysis. The results thus suggest the sensitivity of the model to reflect the nutrient signal response, a nontrivial validation considering the complexity of the system, encouraging even more detailed studies on the thermodynamic quantification of the effects and the identification of the signaling networks.

Protein-protein interaction of RdRp with its co-factor NSP8 and NSP7 to decipher the interface hotspot residues for drug targeting: A comparison between SARS-CoV-2 and SARS-CoV

In this study we explored the molecular mechanism of RdRp (Non-Structural Protein, NSP12) interaction with its co-factors NSP7 and NSP8 which is the main toolbox for RNA replication and transcription of SARS-CoV-2 and SARS-CoV. The replication complex is a heterotetramer consists of one NSP12, one NSP7 and two NSP8. Extensive molecular dynamics (MD) simulations were applied on both the heterotetramer complexes to generate the conformations and were used to estimate the MMPBSA binding free energy (BFE) and per-residue energy decomposition of NSP12-NSP8 and NSP12-NSP7 and NSP7-NSP8 complexes. The BFE of SARS-CoV-2 heterotetramer complex with its corresponding partner protein was significantly higher as compared to SARS-CoV. Interface hotspot residues were predicted using different methods implemented in KFC (Knowledge-based FADA and Contracts), HotRegion and Robetta web servers. Per-residue energy decomposition analysis showed that the predicted interface hotspot residues contribute more energy towards the formation of complexes and most of the predicted hotspot residues are clustered together. However, there is a slight difference in the residue-wise energy contribution in the interface NSPs on heterotetramer viral replication complex of both coronaviruses. While the overall replication complex of SARS-CoV-2 was found to be slightly flexible as compared to SARS-CoV. This difference in terms of structural flexibility/stability and energetic characteristics of interface residues including hotspots at PPI interface in the viral replication complexes may be the reason of higher rate of RNA replication of SARS-CoV-2 as compared to SARS-CoV. Overall, the interaction profile at PPI interface such as, interface area, hotspot residues, nature of bonds and energies between NSPs, may provide valuable insights in designing of small molecules or peptide/peptidomimetic ligands which can fit into the PPI interface to disrupt the interaction.

Molecular Modeling and Experimental Evaluation of Non-Chiral Components of Bergamot Essential Oil with Inhibitory Activity against Human Monoamine Oxidases

Human monoamine oxidases (hMAOs) are well-established targets for the treatment of neurological disorders such as depression, Parkinson's disease and Alzheimer's disease. Despite the efforts carried out over the years, few selective and reversible MAO inhibitors are on the market. Thus, a continuous search for new compounds is needed. Herein, MAO inhibitors were searched among the non-chiral constituents of Bergamot Essential Oil (BEO) with the aid of computational tools. Accordingly, molecular modeling simulations were carried out on both hMAO-A and hMAO-B for the selected constituents. The theoretically predicted target recognition was then used to select the most promising compounds. Among the screened compounds, Bergamottin, a furocoumarin, showed selective hMAO-B inhibitory activity, fitting its active site well. Molecular dynamics simulations were used to deeply analyze the target recognition and to rationalize the selectivity preference. In agreement with the computational results, experimental studies confirmed both the hMAO inhibition properties of Bergamottin and its preference for the isoform B.

Dissipative Particle Dynamics Simulation of Ultrasound Propagation through Liquid Water

Ultrasound is widely used as a noninvasive method in therapeutic and diagnostic applications. These can be further optimized by computational approaches, as they allow for controlled testing and rational optimization of the ultrasound parameters, such as frequency and amplitude. Usually, continuum numerical methods are used to simulate ultrasound propagating through different tissue types. In contrast, ultrasound simulations using particle description are less common, as the implementation is challenging. In this work, a dissipative particle dynamics model is used to perform ultrasound simulations in liquid water. The effects of frequency and thermostat parameters are studied and discussed. We show that frequency and thermostat parameters affect not only the attenuation but also the computed speed of sound. The present study paves the way for development and optimization of a virtual ultrasound machine for large-scale biomolecular simulations.

Solvent-scaling as an alternative to coarse-graining in adaptive-resolution simulations: The adaptive solvent-scaling (AdSoS) scheme

A new approach termed Adaptive Solvent-Scaling (AdSoS) is introduced for performing simulations of a solute embedded in a fine-grained (FG) solvent region itself surrounded by a coarse-grained (CG) solvent region, with a continuous FG ↔ CG switching of the solvent resolution across a buffer layer. Instead of relying on a distinct CG solvent model, the AdSoS scheme is based on CG models defined by a dimensional scaling of the FG solvent by a factor s, accompanied by an s-dependent modulation of the atomic masses and interaction parameters. The latter changes are designed to achieve an isomorphism between the dynamics of the FG and CG models, and to preserve the dispersive and dielectric solvation properties of the solvent with respect to a solute at FG resolution. This scaling approach offers a number of advantages compared to traditional coarse-graining: (i) the CG parameters are immediately related to those of the FG model (no need to parameterize a distinct CG model); (ii) nearly ideal mixing is expected for CG variants with similar s-values (ideal mixing holding in the limit of identical s-values); (iii) the solvent relaxation timescales should be preserved (no dynamical acceleration typical for coarse-graining); (iv) the graining level N_G (number of FG molecules represented by one CG molecule) can be chosen arbitrarily (in particular, N_G = s³ is not necessarily an integer); and (v) in an adaptive-resolution scheme, this level can be varied continuously as a function of the position (without requiring a bundling mechanism), and this variation occurs at a constant number of particles per molecule (no occurrence of fractional degrees of freedom in the buffer layer). By construction, the AdSoS scheme minimizes the thermodynamic mismatch between the different regions of the adaptive-resolution system, leading to a nearly homogeneous scaled solvent density s³ρ. Residual density artifacts in and at the surface of the boundary layer can easily be corrected by means of a grid-based biasing potential constructed in a preliminary pure-solvent simulation. This article introduces the AdSoS scheme and provides an initial application to pure atomic liquids (no solute) with Lennard-Jones plus Coulomb interactions in a slab geometry.

Repurposing of approved drug molecules for viral infectious diseases: a molecular modelling approach

The identification of new viral drugs has become a task of paramount significance due to the frequent occurrence of viral infections and especially during the current pandemic. Despite the recent advancements, the development of antiviral drugs has not made parallel progress. Reduction of time frame and cost of the drug development process is the major advantage of drug repurposing. Therefore, in this study, a drug repurposing strategy using molecular modelling techniques, i.e. biological activity prediction, virtual screening, and molecular dynamics simulation was employed to find promising repurposing candidates for viral infectious diseases. The biological activities of non-redundant (4171) drug molecules were predicted using PASS analysis, and 1401 drug molecules were selected which showed antiviral activities in the analysis. These drug molecules were subjected to virtual screening against the selected non-structural viral proteins. A series of filters, i.e. top 10 drug molecules based on binding affinity, mean value of binding affinity, visual inspection of protein-drug complexes, and number of H-bond between protein and drug molecules were used to narrow down the drug molecules. Molecular dynamics simulation analysis was carried out to validate the intrinsic atomic interactions and binding conformations of protein-drug complexes. The binding free energies of drug molecules were assessed by employing MMPBSA analysis. Finally, nine drug molecules were prioritized, as promising repurposing candidates with the potential to inhibit the selected non-structural viral proteins.Communicated by Ramaswamy H. Sarma.

Rotational dynamics of proteins in nanochannels: role of solvent's local viscosity

Viscosity variation of solvent in local regions near a solid surface, be it a biological surface of a protein or an engineered surface of a nanoconfinement, is a direct consequence of intermolecular interactions between the solid body and the solvent. The current coarse-grained molecular dynamics study takes advantage of this phenomenon to investigate the anomaly in a solvated protein's rotational dynamics confined using a representative solid matrix. The concept of persistence time, the characteristic time of structural reordering in liquids, is used to compute the solvent's local viscosity. With an increase in the degree of confinement, the confining matrix significantly influences the solvent molecule's local viscosity present in the protein hydration layer through intermolecular interactions. This effect contributes to the enhanced drag force on protein motion, causing a reduction in the rotational diffusion coefficient. Simulation results suggest that the direct matrix-protein non-bonded interaction is responsible for the occasional jump and discontinuity in orientational motion when the protein is in very tight confinement.

Surface Shear Viscosity and Interleaflet Friction from Nonequilibrium Simulations of Lipid Bilayers

Nonequilibrium simulation protocols based on shear deformations are applied to determine the surface viscosity and interleaflet friction of lipid bilayers. At high shear rates, a non-Newtonian shear thinning regime is observed, but lower shear rates yield a Newtonian plateau and results that are consistent with equilibrium measurements based on fluctuation-dissipation theorems. Application to all-atom bilayers modeled with the CHARMM36 parameter set yields values for the surface viscosity that are consistent with microscopic measurements based on membrane protein diffusion but are approximately 10 times lower than more macroscopic experimental measurements. The interleaflet friction is about 10 times lower than experimental measurements. Trends across different lipids, temperatures, and ternary liquid-disordered phase mixtures produce results that are consistent with experimental diffusion constants. Application of the protocol to the liquid-ordered phase fails to yield a Newtonian plateau, suggesting more complex rheology.

SWINGER: a clustering algorithm for concurrent coupling of atomistic and supramolecular liquids

In this contribution, we review recent developments and applications of a dynamic clustering algorithm SWINGER tailored for the multiscale molecular simulations of biomolecular systems. The algorithm on-the-fly redistributes solvent molecules among supramolecular clusters. In particular, we focus on its applications in combination with the adaptive resolution scheme, which concurrently couples atomistic and coarse-grained molecular representations. We showcase the versatility of our multiscale approach on a few applications to biomolecular systems coupling atomistic and supramolecular water models such as the well-established MARTINI and dissipative particle dynamics models and provide an outlook for future work.

Adaptive resolution simulations coupling atomistic water to dissipative particle dynamics

Multiscale methods are the most efficient way to address the interlinked spatiotemporal scales encountered in soft matter and molecular liquids. In the literature reported hybrid approaches span from quantum to atomistic, coarse-grained, and continuum length scales. In this article, we present the hybrid coupling of the molecular dynamics (MD) and dissipative particle dynamics (DPD) methods, bridging the micro- and mesoscopic descriptions. The interfacing is performed within the adaptive resolution scheme (AdResS), which is a linear momentum conserving coupling technique. Our methodology is hence suitable to simulate fluids on the micro/mesoscopic scale, where hydrodynamics plays an important role. The presented approach is showcased for water at ambient conditions. The supramolecular coupling is enabled by a recently developed clustering algorithm SWINGER that assembles, disassembles, and reassembles clusters as needed during the course of the simulation. This allows for a seamless coupling between standard atomistic MD and DPD models. The developed framework can be readily applied to various applications in the fields of materials and life sciences, e.g., simulations of phospholipids and polymer melts, or to study the red blood cells behavior in normal and disease states.

Molecular Mechanism of Uptake of Cationic Photoantimicrobial Phthalocyanine across Bacterial Membranes Revealed by Molecular Dynamics Simulations

Phthalocyanines are aromatic macrocyclic compounds, which are structurally related to porphyrins. In clinical practice, phthalocyanines are used in fluorescence imaging and photodynamic therapy of cancer and noncancer lesions. Certain forms of the substituted polycationic metallophthalocyanines have been previously shown to be active in photodynamic inactivation of both Gram-negative and Gram-positive bacteria; one of them is zinc octakis(cholinyl)phthalocyanine (ZnPcChol⁸⁺). However, the molecular details of how these compounds translocate across bacterial membranes still remain unclear. In the present work, we have developed a coarse-grained (CG) molecular model of ZnPcChol⁸⁺ within the framework of the popular MARTINI CG force field. The obtained model was used to probe the solvation behavior of phthalocyanine molecules, which agreed with experimental results. Subsequently, it was used to investigate the molecular details of interactions between phthalocyanines and membranes of various compositions. The results demonstrate that ZnPcChol⁸⁺ has high affinity to both the inner and the outer model membranes of Gram-negative bacteria, although this species does not show noticeable affinity to the 1-palmitoyl-2-oleoyl- sn-glycero-3-phosphatidylcholine membrane. Furthermore, we found out that the process of ZnPcChol⁸⁺ penetration toward the center of the outer bacterial membrane is energetically favorable and leads to its overall disturbance and formation of the aqueous pore. Such intramembrane localization of ZnPcChol⁸⁺ suggests their twofold cytotoxic effect on bacterial cells: (1) via induction of lipid peroxidation by enhanced production of reactive oxygen species (i.e., photodynamic toxicity); (2) via rendering the bacterial membrane more permeable for additional Pc molecules as well as other compounds. We also found that the kinetics of penetration depends on the presence of phospholipid defects in the lipopolysaccharide leaflet of the outer membrane and the type of counterions, which stabilize it. Thus, the results of our simulations provide a detailed molecular view of ZnPcChol⁸⁺ "self-promoted uptake", the pathway previously proposed for some small molecules crossing the outer bacterial membrane.

Multiscale Simulation of Protein Hydration Using the SWINGER Dynamical Clustering Algorithm

To perform computationally efficient concurrent multiscale simulations of biological macromolecules in solution, where the all-atom (AT) models are coupled to supramolecular coarse-grained (SCG) solvent models, previous studies resorted to modified AT water models, such as the bundled-simple point charge (SPC) models, that use semiharmonic springs to restrict the relative movement of water molecules within a cluster. Those models can have a significant impact on the simulated biomolecules and can lead, for example, to a partial unfolding of a protein. In this work, we employ the recently developed alternative approach with a dynamical clustering algorithm, SWINGER, which enables a direct coupling of original unmodified AT and SCG water models. We perform an adaptive resolution molecular dynamics simulation of a Trp-Cage miniprotein in multiscale water, where the standard SPC water model is interfaced with the widely used MARTINI SCG model, and demonstrate that, compared to the corresponding full-blown AT simulations, the structural and dynamic properties of the solvated protein and surrounding solvent are well reproduced by our approach.

Hybrid All-Atom/Coarse-Grained Simulations of Proteins by Direct Coupling of CHARMM and PRIMO Force Fields

Hybrid all-atom/coarse-grained (AA/CG) simulations of proteins offer a computationally efficient compromise where atomistic details are only applied to biologically relevant regions while benefiting from the speedup of treating the remaining parts of a given system at the CG level. The recently developed CG model, PRIMO, allows a direct coupling with an atomistic force field with no additional modifications or coupling terms and the ability to carry out dynamic simulations without any restraints on secondary or tertiary structures. A hybrid AA/CG scheme based on combining all-atom CHARMM and coarse-grained PRIMO representations was validated via molecular dynamics and replica exchange simulations of soluble and membrane proteins. The AA/CG scheme was also tested in the calculation of the free energy profile for the transition from the closed to the open state of adenylate kinase via umbrella sampling molecular dynamics method. The overall finding is that the AA/CG scheme generates dynamics and energetics that are qualitatively and quantitatively comparable to AA simulations while offering the computational advantages of coarse-graining. This model opens the door to challenging applications where high accuracy is required only in parts of large biomolecular complexes.

Adaptive resolution simulations of biomolecular systems

In this review article, we discuss and analyze some recently developed hybrid atomistic-mesoscopic solvent models for multiscale biomolecular simulations. We focus on the biomolecular applications of the adaptive resolution scheme (AdResS), which allows solvent molecules to change their resolution back and forth between atomistic and coarse-grained representations according to their positions in the system. First, we discuss coupling of atomistic and coarse-grained models of salt solution using a 1-to-1 molecular mapping-i.e., one coarse-grained bead represents one water molecule-for development of a multiscale salt solution model. In order to make use of coarse-grained molecular models that are compatible with the MARTINI force field, one has to resort to a supramolecular mapping, in particular to a 4-to-1 mapping, where four water molecules are represented with one coarse-grained bead. To this end, bundled atomistic water models are employed, i.e., the relative movement of water molecules that are mapped to the same coarse-grained bead is restricted by employing harmonic springs. Supramolecular coupling has recently also been extended to polarizable coarse-grained water models with explicit charges. Since these coarse-grained models consist of several interaction sites, orientational degrees of freedom of the atomistic and coarse-grained representations are coupled via a harmonic energy penalty term. The latter aligns the dipole moments of both representations. The reviewed multiscale solvent models are ready to be used in biomolecular simulations, as illustrated in a few examples.

Diffusion of Integral Membrane Proteins in Protein-Rich Membranes

The lateral diffusion of embedded proteins along lipid membranes in protein-poor conditions has been successfully described in terms of the Saffman-Delbrück (SD) model, which predicts that the protein diffusion coefficient D is weakly dependent on its radius R as D ∝ ln(1/R). However, instead of being protein-poor, native cell membranes are extremely crowded with proteins. On the basis of extensive molecular simulations, we here demonstrate that protein crowding of the membrane at physiological levels leads to deviations from the SD relation and to the emergence of a stronger Stokes-like dependence D ∝ 1/R. We propose that this 1/R law mainly arises due to geometrical factors: smaller proteins are able to avoid confinement effects much better than their larger counterparts. The results highlight that the lateral dynamics in the crowded setting found in native membranes is radically different from protein-poor conditions and plays a significant role in formation of functional multiprotein complexes.

Combining the MARTINI and Structure-Based Coarse-Grained Approaches for the Molecular Dynamics Studies of Conformational Transitions in Proteins

The application of coarse-grained (CG) models in biology is essential to access large length and time scales required for the description of many biological processes. The ELNEDIN protein model is based on the well-known MARTINI CG force-field and incorporates additionally harmonic bonds of a certain spring constant within a defined cutoff distance between pairs of residues, in order to preserve the native structure of the protein. In this case, the use of unbreakable harmonic bonds hinders the study of unfolding and folding processes. To overcome this barrier we have replaced the harmonic bonds with Lennard-Jones interactions based on the contact map of the native protein structure as is done in Go̅-like models. This model exhibits very good agreement with all-atom simulations and the ELNEDIN. Moreover, it can capture the structural motion linked to particular catalytic activity in the Man5B protein, in agreement with all-atom simulations. In addition, our model is based on the van der Waals radii, instead of a cutoff distance, which results in a smaller contact map. In conclusion, we anticipate that our model will provide further possibilities for studying biological systems based on the MARTINI CG force-field by using advanced-sampling methods, such as parallel tempering and metadynamics.

Molecular Dynamics Study of the Hydrophilic-to-Hydrophobic Switching in the Wettability of a Gold Surface Corrugated with Spherical Cavities

This paper reports a large scale molecular dynamics (MD) simulation study of the wettability of a gold surface engraved with (hemi)spherical cavities. By increasing the depth of cavities, the contact angle (CA) of a water droplet on the surface was varied from a hydrophilic (69°) to a hydrophobic value (>109°). The nonmonotonic behavior of the CA vs the depth of the cavities was consistent with the Cassie-Baxter theory, as found in the experiment by Abdelsalam et al. (Abdelsalam, M. E.; Bartlett, P. N.; Kelf, T.; Baumberg, J. Wetting of Regularly Structured Gold Surfaces. Langmuir 2005, 21, 1753-1757). Depending on the depth of cavities, however, the droplet existed not only in the Cassie-Baxter state, but also in the Wenzel or an intermediate state, where the cavities were penetrated partially by the droplet.

Adaptive Resolution Simulation of Supramolecular Water: The Concurrent Making, Breaking, and Remaking of Water Bundles

The adaptive resolution scheme (AdResS) is a multiscale molecular dynamics simulation approach that can concurrently couple atomistic (AT) and coarse-grained (CG) resolution regions, i.e., the molecules can freely adapt their resolution according to their current position in the system. Coupling to supramolecular CG models, where several molecules are represented as a single CG bead, is challenging, but it provides higher computational gains and connection to the established MARTINI CG force field. Difficulties that arise from such coupling have been so far bypassed with bundled AT water models, where additional harmonic bonds between oxygen atoms within a given supramolecular water bundle are introduced. While these models simplify the supramolecular coupling, they also cause in certain situations spurious artifacts, such as partial unfolding of biomolecules. In this work, we present a new clustering algorithm SWINGER that can concurrently make, break, and remake water bundles and in conjunction with the AdResS permits the use of original AT water models. We apply our approach to simulate a hybrid SPC/MARTINI water system and show that the essential properties of water are correctly reproduced with respect to the standard monoscale simulations. The developed hybrid water model can be used in biomolecular simulations, where a significant speed up can be obtained without compromising the accuracy of the AT water model.

Systematic evaluation of bundled SPC water for biomolecular simulations

How accurate is bundled SPC water as inner shell solvent for hybrid all-atom/coarse-grained simulations?