Screening of Active Substances Regulating Alzheimer's Disease in Ginger and Visualization of the Effectiveness on 6-Gingerol Pathway Targets

Ginger has been reported to potentially treat Alzheimer's disease (AD), but the specific compounds responsible for this biological function and their mechanisms are still unknown. In this study, a combination of network pharmacology, molecular docking, and dynamic simulation technology was used to screen active substances that regulate AD and explore their mechanisms. The TCMSP, GeneCards, OMIM, and DisGeNET databases were utilized to obtain 95 cross-targets related to ginger's active ingredients and AD as key targets. A functional enrichment analysis revealed that the pathways in which ginger's active substances may be involved in regulating AD include response to exogenous stimuli, response to oxidative stress, response to toxic substances, and lipid metabolism, among others. Furthermore, a drug-active ingredient-key target interaction network diagram was constructed, highlighting that 6-Gingerol is associated with 16 key targets. Additionally, a protein-protein interaction (PPI) network was mapped for the key targets, and HUB genes (ALB, ACTB, GAPDH, CASP3, and CAT) were identified. Based on the results of network pharmacology and cell experiments, 6-Gingerol was selected as the active ingredient for further investigation. Molecular docking was performed between 6-Gingerol and its 16 key targets, and the top three proteins with the strongest binding affinities (ACHE, MMP2, and PTGS2) were chosen for molecular dynamics analysis together with the CASP3 protein as the HUB gene. The findings indicate that 6-Gingerol exhibits strong binding ability to these disease targets, suggesting its potential role in regulating AD at the molecular level, as well as in abnormal cholinesterase metabolism and cell apoptosis, among other related regulatory pathways. These results provide a solid theoretical foundation for future in vitro experiments using actual cells and animal experiments to further investigate the application of 6-Gingerol.

Visualizing the impact of disease-associated mutations on G protein-nucleotide interactions

Activation of G proteins stimulates ubiquitous intracellular signaling cascades essential for life processes. Under normal physiological conditions, nucleotide exchange is initiated upon the formation of complexes between a G protein and G protein-coupled receptor (GPCR), which facilitates exchange of bound GDP for GTP, subsequently dissociating the trimeric G protein into its Gα and Gβγ subunits. However, single point mutations in Gα circumvent nucleotide exchange regulated by GPCR-G protein interactions, leading to either loss-of-function or constitutive gain-of-function. Mutations in several Gα subtypes are closely linked to the development of multiple diseases, including several intractable cancers. We leveraged an integrative spectroscopic and computational approach to investigate the mechanisms by which seven of the most frequently observed clinically-relevant mutations in the α subunit of the stimulatory G protein result in functional changes. Variable temperature circular dichroism (CD) spectroscopy showed a bimodal distribution of thermal melting temperatures across all GαS variants. Modeling from molecular dynamics (MD) simulations established a correlation between observed thermal melting temperatures and structural changes caused by the mutations. Concurrently, saturation-transfer difference NMR (STD-NMR) highlighted variations in the interactions of GαS variants with bound nucleotides. MD simulations indicated that changes in local interactions within the nucleotide-binding pocket did not consistently align with global structural changes. This collective evidence suggests a multifaceted energy landscape, wherein each mutation may introduce distinct perturbations to the nucleotide-binding site and protein-protein interaction sites. Consequently, it underscores the importance of tailoring therapeutic strategies to address the unique challenges posed by individual mutations.

Structure and Function of Canine SP-C Mimic Proteins in Synthetic Surfactant Lipid Dispersions

Lung surfactant is a mixture of lipids and proteins and is essential for air breathing in mammals. The hydrophobic surfactant proteins B and C (SP-B and SP-C) assist in reducing surface tension in the lung alveoli by organizing the surfactant lipids. SP-B deficiency is life-threatening, and a lack of SP-C can lead to progressive interstitial lung disease. B-YL (41 amino acids) is a highly surface-active, sulfur-free peptide mimic of SP-B (79 amino acids) in which the four cysteine residues are replaced by tyrosine. Mammalian SP-C (35 amino acids) contains two cysteine-linked palmitoyl groups at positions 5 and 6 in the N-terminal region that override the β-sheet propensities of the native sequence. Canine SP-C (34 amino acids) is exceptional because it has only one palmitoylated cysteine residue at position 4 and a phenylalanine at position 5. We developed canine SP-C constructs in which the palmitoylated cysteine residue at position 4 is replaced by phenylalanine (SP-Cff) or serine (SP-Csf) and a glutamic acid-lysine ion-lock was placed at sequence positions 20-24 of the hydrophobic helical domain to enhance its alpha helical propensity. AI modeling, molecular dynamics, circular dichroism spectroscopy, Fourier Transform InfraRed spectroscopy, and electron spin resonance studies showed that the secondary structure of canine SP-Cff ion-lock peptide was like that of native SP-C, suggesting that substitution of phenylalanine for cysteine has no apparent effect on the secondary structure of the peptide. Captive bubble surfactometry demonstrated higher surface activity for canine SP-Cff ion-lock peptide in combination with B-YL in surfactant lipids than with canine SP-Csf ion-lock peptide. These studies demonstrate the potential of canine SP-Cff ion-lock peptide to enhance the functionality of the SP-B peptide mimic B-YL in synthetic surfactant lipids.

Elucidating Interfacial Dynamics of Ti-Al Systems Using Molecular Dynamics Simulation and Markov State Modeling

Due to their remarkable mechanical and chemical properties, Ti-Al-based materials are attracting considerable interest in numerous fields of engineering, such as automotive, aerospace, and defense. With their low density, high strength, and resistance to corrosion and oxidation, these intermetallic alloys and metal-compound composites have found diverse applications. However, additive manufacturing and heat treatment of Ti-Al alloys frequently lead to brittleness and severe formation of defects. The present study delves into the interfacial dynamics of these Ti-Al systems, particularly focusing on the behavior of Ti and Al atoms in the presence of TiAl3 grain boundaries under experimental heat treatment conditions. Using a combination of molecular dynamics and Markov state modeling, we scrutinize the kinetic processes involved in the formation of TiAl3. The molecular dynamics simulation indicates that at the early stage of heat treatment, the predominating process is the diffusion of Al atoms toward the Ti surface through the TiAl3 grain boundaries. Markov state modeling identifies three distinct dynamic states of Al atoms within the Ti/Al mixture that forms during the process, each exhibiting a unique spatial distribution. Using transition time scales as a qualitative measure of the rapidness of the dynamics, it is observed that the Al dynamics is significantly less rapid near the Ti surface compared to the Al surface. Put together, the results offer a comprehensive understanding of the interfacial dynamics and reveal a three-stage diffusion mechanism. The process initiates with the premelting of Al, proceeds with the prevalent diffusion of Al atoms toward the Ti surface, and eventually ceases as the Ti concentration within the mixture progressively increases. The insights gained from this study could contribute significantly to the control and optimization of manufacturing processes for these high-performing Ti-Al-based materials.

EnGens: a computational framework for generation and analysis of representative protein conformational ensembles

Proteins are dynamic macromolecules that perform vital functions in cells. A protein structure determines its function, but this structure is not static, as proteins change their conformation to achieve various functions. Understanding the conformational landscapes of proteins is essential to understand their mechanism of action. Sets of carefully chosen conformations can summarize such complex landscapes and provide better insights into protein function than single conformations. We refer to these sets as representative conformational ensembles. Recent advances in computational methods have led to an increase in the number of available structural datasets spanning conformational landscapes. However, extracting representative conformational ensembles from such datasets is not an easy task and many methods have been developed to tackle it. Our new approach, EnGens (short for ensemble generation), collects these methods into a unified framework for generating and analyzing representative protein conformational ensembles. In this work, we: (1) provide an overview of existing methods and tools for representative protein structural ensemble generation and analysis; (2) unify existing approaches in an open-source Python package, and a portable Docker image, providing interactive visualizations within a Jupyter Notebook pipeline; (3) test our pipeline on a few canonical examples from the literature. Representative ensembles produced by EnGens can be used for many downstream tasks such as protein-ligand ensemble docking, Markov state modeling of protein dynamics and analysis of the effect of single-point mutations.

Screening and Analysis of Possible Drugs Binding to PDGFRα: A Molecular Modeling Study

The platelet-derived growth factor receptor (PDGFR) is a membrane tyrosine kinase receptor involved in several metabolic pathways, not only physiological but also pathological, as in tumor progression, immune-mediated diseases, and viral diseases. Considering this macromolecule as a druggable target for modulation/inhibition of these conditions, the aim of this work was to find new ligands or new information to design novel effective drugs. We performed an initial interaction screening with the human intracellular PDGFRα of about 7200 drugs and natural compounds contained in 5 independent databases/libraries implemented in the MTiOpenScreen web server. After the selection of 27 compounds, a structural analysis of the obtained complexes was performed. Three-dimensional quantitative structure-activity relationship (3D-QSAR) and absorption, distribution, metabolism, excretion, and toxicity (ADMET) analyses were also performed to understand the physicochemical properties of identified compounds to increase affinity and selectivity for PDGFRα. Among these 27 compounds, the drugs Bafetinib, Radotinib, Flumatinib, and Imatinib showed higher affinity for this tyrosine kinase receptor, lying in the nanomolar order, while the natural products included in this group, such as curcumin, luteolin, and epigallocatechin gallate (EGCG), showed sub-micromolar affinities. Although experimental studies are mandatory to fully understand the mechanisms behind PDGFRα inhibitors, the structural information obtained through this study could provide useful insight into the future development of more effective and targeted treatments for PDGFRα-related diseases, such as cancer and fibrosis.

Molecular Understanding of the Interfacial Interaction and Corrosion Resistance between Epoxy Adhesive and Metallic Oxides on Galvanized Steel

The epoxy adhesive-galvanized steel adhesive structure has been widely used in various industrial fields, but achieving high bonding strength and corrosion resistance is a challenge. This study examined the impact of surface oxides on the interfacial bonding performance of two types of galvanized steel with Zn-Al or Zn-Al-Mg coatings. Scanning electron microscopy and X-ray photoelectron spectroscopy analysis showed that the Zn-Al coating was covered by ZnO and Al₂O₃, while MgO was additionally found on the Zn-Al-Mg coating. Both coatings exhibited excellent adhesion in dry environments, but after 21 days of water soaking, the Zn-Al-Mg joint demonstrated better corrosion resistance than the Zn-Al joint. Numerical simulations revealed that metallic oxides of ZnO, Al₂O₃, and MgO had different adsorption preferences for the main components of the adhesive. The adhesion stress at the coating-adhesive interface was mainly due to hydrogen bonds and ionic interactions, and the theoretical adhesion stress of MgO adhesive system was higher than that of ZnO and Al₂O₃. The corrosion resistance of the Zn-Al-Mg adhesive interface was mainly due to the stronger corrosion resistance of the coating itself, and the lower water-related hydrogen bond content at the MgO adhesive interface. Understanding these bonding mechanisms can lead to the development of improved adhesive-galvanized steel structures with enhanced corrosion resistance.

Current Trends and Changes in Use of Membrane Molecular Dynamics Simulations within Academia and the Pharmaceutical Industry

There has been an almost exponential increase in the use of molecular dynamics simulations in basic research and industry over the last 5 years, with almost a doubling in the number of publications each year. Many of these are focused on neurological membranes, and biological membranes in general, applied to the medical industry. A smaller portion have utilized membrane simulations to answer more basic questions related to the function of specific proteins, chemicals or biological processes. This review covers some newer studies, alongside studies from the last two decades, to determine changes in the field. Some of these are basic, while others are more profound, such as multi-component embedded membrane machinery. It is clear that many facets of the discipline remain the same, while the focus on and uses of the technology are broadening in scope and utilization as a general research tool. Analysis of recent literature provides an overview of the current methodologies, covers some of the recent trends or advances and tries to make predictions of the overall path membrane molecular dynamics will follow in the coming years. In general, the overview presented is geared towards the general scientific community, who may wish to introduce the use of these methodologies in light of these changes, making molecular dynamic simulations more feasible for general scientific or medical research.

Probing the Efficiency of 13-Pyridylalkyl Berberine Derivatives to Human Telomeric G-Quadruplexes Binding: Spectroscopic, Solid State and In Silico Analysis

The interaction between the series of berberine derivatives 1-5 (NAX071, NAX120, NAX075, NAX077 and NAX079) and human telomeric G-quadruplexes (G4), which are able to inhibit the Telomerase enzyme's activity in malignant cells, was investigated. The derivatives bear a pyridine moiety connected by a hydrocarbon linker of varying length (n = 1-5, with n number of aliphatic carbon atoms) to the C13 position of the parent berberine. As for the G4s, both bimolecular 5'-TAGGGTTAGGGT-3' (Tel12) and monomolecular 5'-TAGGGTTAGGGTTAGGGTTAGGG-3' (Tel23) DNA oligonucleotides were considered. Spectrophotometric titrations, melting tests, X-ray diffraction solid state analysis and in silico molecular dynamics (MD) simulations were used to describe the different systems. The results were compared in search of structure-activity relationships. The analysis pointed out the formation of 1:1 complexes between Tel12 and all ligands, whereas both 1:1 and 2:1 ligand/G4 stoichiometries were found for the adduct formed by NAX071 (n = 1). Tel12, with tetrads free from the hindrance by the loop, showed a higher affinity. The details of the different binding geometries were discussed, highlighting the importance of H-bonds given by the berberine benzodioxole group and a correlation between the strength of binding and the hydrocarbon linker length. Theoretical (MD) and experimental (X-ray) structural studies evidence the possibility for the berberine core to interact with one or both G4 strands, depending on the constraints given by the linker length, thus affecting the G4 stabilization effect.

A Core-Shell Approach for Systematically Coarsening Nanoparticle-Membrane Interactions: Application to Silver Nanoparticles

The continuous release of engineered nanomaterial (ENM) into the environment may bring about health concerns following human exposure. One important source of ENMs are silver nanoparticles (NPs) that are extensively used as anti-bacterial additives. The introduction of ENMs into the human body can occur via ingestion, skin uptake or the respiratory system. Therefore, evaluating how NPs translocate over bio-membranes is essential in assessing their primary toxicity. Unfortunately, data regarding membrane-NP interaction is still scarce, as is theoretical and in silico insight into what governs adhesion and translocation for the most relevant NPs and membranes. Coarse-grained (CG) molecular descriptions have the potential to alleviate this situation, but are hampered by the absence of a direct link to NP materials and membrane adhesion mechanisms. Here, we interrogate the relationship between the most common NP representation at the CG level and the adhesion characteristics of a model lung membrane. We find that this representation for silver NPs is non-transferable, meaning that a proper CG representation for one size is not suited for other sizes. We also identify two basic types of primary adhesion-(partial) NPs wrapping by the membrane and NP insertion into the membrane-that closely relate to the overall NP hydrophobicity and significantly differ in terms of lipid coatings. The proven non-transferability of the standard CG representation with size forms an inspiration for introducing a core-shell model even for bare NPs that are uniform in composition. Using existing all-atom molecular dynamics (MD) data as a reference, we show that this extension does allow us to reproduce size-dependent NP adhesion properties and lipid responses to NP binding at the CG level. The subsequent CGMD evaluation for 10 nm Ag NPs provides new insight into membrane binding for relevant NP sizes and into the role of water in trapping NPs into defected mixed monolayer-bilayer states. This development will be instrumental for simulating NP-membrane adhesion towards more experimentally relevant length and time scales for particular NP materials.

N-glycosylation modulates enzymatic activity of Trypanosoma congolense trans-sialidase

Trypanosomes cause the devastating disease trypanosomiasis, in which the action of trans-sialidase (TS) enzymes harbored on their surface is a key virulence factor. TS enzymes are N-glycosylated, but the biological functions of their glycans have remained elusive. In this study, we investigated the influence of N-glycans on the enzymatic activity and structural stability of TconTS1, a recombinant TS from the African parasite Trypanosoma congolense. We expressed the enzyme in Chinese hamster ovary Lec1 cells, which produce high-mannose type N-glycans similar to the TS N-glycosylation pattern in vivo. Our MALDI-TOF mass spectrometry data revealed that up to eight putative N-glycosylation sites were glycosylated. In addition, we determined that N-glycan removal via endoglycosidase H_f treatment of TconTS1 led to a decrease in substrate affinity relative to the untreated enzyme but had no impact on the conversion rate. Furthermore, we observed no changes in secondary structure elements of hypoglycosylated TconTS1 in CD experiments. Finally, our molecular dynamics simulations provided evidence for interactions between monosaccharide units of the highly flexible N-glycans and some conserved amino acids located at the catalytic site. These interactions led to conformational changes, possibly enhancing substrate accessibility and enzyme–substrate complex stability. The here-observed modulation of catalytic activity via N-glycans represents a so-far-unknown structure–function relationship potentially inherent in several members of the TS enzyme family.

Actions of Novel Angiotensin Receptor Blocking Drugs, Bisartans, Relevant for COVID-19 Therapy: Biased Agonism at Angiotensin Receptors and the Beneficial Effects of Neprilysin in the Renin Angiotensin System

Angiotensin receptor blockers (ARBs) used in the treatment of hypertension and potentially in SARS-CoV-2 infection exhibit inverse agonist effects at angiotensin AR1 receptors, suggesting the receptor may have evolved to accommodate naturally occurring angiotensin ‘antipeptides’. Screening of the human genome has identified a peptide (EGVYVHPV) encoded by mRNA, complementary to that encoding ANG II itself, which is an inverse agonist. Thus, opposite strands of DNA encode peptides with opposite effects at AR1 receptors. Agonism and inverse agonism at AR1 receptors can be explained by a receptor ‘switching’ between an activated state invoking receptor dimerization/G protein coupling and an inverse agonist state mediated by an alternative/second messenger that is slow to reverse. Both receptor states appear to be driven by the formation of the ANG II charge-relay system involving TyrOH-His/imidazole-Carboxylate (analogous to serine proteases). In this system, tyrosinate species formed are essential for activating AT1 and AT2 receptors. ANGII is also known to bind to the zinc-coordinated metalloprotease angiotensin converting enzyme 2 (ACE2) used by the COVID-19 virus to enter cells. Here we report in silico results demonstrating the binding of a new class of anionic biphenyl-tetrazole sartans (‘Bisartans’) to the active site zinc atom of the endopeptidase Neprilysin (NEP) involved in regulating hypertension, by modulating humoral levels of beneficial vasoactive peptides in the RAS such as vasodilator angiotensin (1–7). In vivo and modeling evidence further suggest Bisartans can inhibit ANG II-induced pulmonary edema and may be useful in combatting SARS-CoV-2 infection by inhibiting ACE2-mediated viral entry to cells.

Deformation Mechanism of Depositing Amorphous Cu-Ta Alloy Film via Nanoindentation Test

As a representative of immiscible alloy systems, the Cu-Ta system was the research topic because of its potential application in industry, military and defense fields. In this study, an amorphous Cu-Ta alloy film was manufactured through magnetron sputter deposition, which was characterized by scanning electron microscopy (SEM) and transmission electron microscopy (TEM). Mechanical properties of Cu-Ta film were detected by the nanoindentation method, which show that the elastic modulus of Cu3.5Ta96.5 is 156.7 GPa, and the hardness is 14.4 GPa. The nanoindentation process was also simulated by molecular dynamic simulation to indicate the deformation mechanism during the load-unload stage. The simulation results show that the structure <0,2,8,4> and <0,2,8,5> Voronoi cells decreased by 0.1% at 50 Ps and then remained at this value during the nanoindentation process. In addition, the number of dislocations vary rapidly with the depth between indenter and surface. Based on the experimental and simulation results, the Voronoi structural changes and dislocation motions are the key reasons for the crystallization of amorphous alloys when loads are applied.

Discovery of novel acetylcholinesterase inhibitors through integration of machine learning with genetic algorithm based in silico screening approaches

Introduction

Alzheimer's disease (AD) is the most studied progressive eurodegenerative disorder, affecting 40-50 million of the global population. This progressive neurodegenerative disease is marked by gradual and irreversible declines in cognitive functions. The unavailability of therapeutic drug candidates restricting/reversing the progression of this dementia has severed the existing challenge. The development of acetylcholinesterase (AChE) inhibitors retains a great research focus for the discovery of an anti-Alzheimer drug.

Materials and methods

This study focused on finding AChE inhibitors by applying the machine learning (ML) predictive modeling approach, which is an integral part of the current drug discovery process. In this study, we have extensively utilized ML and other in silico approaches to search for an effective lead molecule against AChE.

Result and discussion

The output of this study helped us to identify some promising AChE inhibitors. The selected compounds performed well at different levels of analysis and may provide a possible pathway for the future design of potent AChE inhibitors.

A Conserved Structural Role for the Walker-A Lysine in P-Loop Containing Kinases

Bacterial tyrosine kinases (BY-kinases) and shikimate kinases (SKs) comprise two structurally divergent P-loop containing enzyme families that share similar catalytic site geometries, most notably with respect to their Walker-A, Walker-B, and DxD motifs. We had previously demonstrated that in BY-kinases, a specific interaction between the Walker-A and Walker-B motifs, driven by the conserved “catalytic” lysine housed on the former, leads to a conformation that is unable to efficiently coordinate Mg²⁺•ATP and is therefore incapable of chemistry. Here, using enhanced sampling molecular dynamics simulations, we demonstrate that structurally similar interactions between the Walker-A and Walker-B motifs, also mediated by the catalytic lysine, stabilize a state in SKs that deviates significantly from one that is necessary for the optimal coordination of Mg²⁺•ATP. This structural role of the Walker-A lysine is a general feature in SKs and is found to be present in members that encode a Walker-B sequence characteristic of the family (Coxiella burnetii SK), and in those that do not (Mycobacterium tuberculosis SK). Thus, the structural role of the Walker-A lysine in stabilizing an inactive state, distinct from its catalytic function, is conserved between two distantly related P-loop containing kinase families, the SKs and the BY-kinases. The universal conservation of this element, and of the key characteristics of its associated interaction partners within the Walker motifs of P-loop containing enzymes, suggests that this structural role of the Walker-A lysine is perhaps a widely deployed regulatory mechanism within this ancient family.

Understanding Plant Biomass via Computational Modeling

Plant biomass, especially wood, has been used for structural materials since ancient times. It is also showing great potential for new structural materials and it is the major feedstock for the emerging biorefineries for building a sustainable society. The plant cell wall is a hierarchical matrix of mainly cellulose, hemicellulose, and lignin. Herein, the structure, properties, and reactions of cellulose, lignin, and wood cell walls, studied using density functional theory (DFT) and molecular dynamics (MD), which are the widely used computational modeling approaches, are reviewed. Computational modeling, which has played a crucial role in understanding the structure and properties of plant biomass and its nanomaterials, may serve a leading role on developing new hierarchical materials from biomass in the future.

Computational basis of SARS-CoV 2 main protease inhibition: an insight from molecular dynamics simulation based findings

The coronavirus disease 2019 (COVID-19) pandemic is caused by newly discovered severe acute respiratory syndrome-coronavirus 2 (SARS-CoV-2). One of the striking targets amongst all the proteins in coronavirus is the main protease (M^pro), as it plays vital biological roles in replication and maturation of the virus, and hence the potential target. The aim of this study is to repurpose the Food and Drug Administration (FDA) approved molecules via computer-aided drug designing against M^pro (PDB ID: 6Y2F) of SARS CoV-2 due to its high x-ray resolution of 1.95 Å as compared to other published M^prostructures. High Through Virtual Screening (HTVS) of 2456 FDA approved drugs using structure-based docking were analyzed. Molecular Dynamics simulations were performed to check the overall structural stability (RMSD), Cα fluctuations (RMSF) and protein-ligand interactions. Further, trajectory analysis was performed to assess the binding quality by exploiting the protein-residue motion cross correlation (DCCM) and binding free energy (MM/GBSA). Tenofovir, an antiretroviral for HIV-proteases and Terlipressin, a vasoconstrictor show stable RMSD, RMSF, better MM/GBSA with good cross correlation as compared to the Apo and O6K. Moreover, the results show concurrence with Nelfinavir, Lopinavir and Ritonavir which have shown significant inhibition in in vitro studies. Therefore, we conclude that Tenofovir and Terlipresssin might also show protease inhibition but are still open to clinical validation in case of SARS-CoV 2 treatment.Communicated by Ramaswamy H. Sarma.

Structural Basis of Inhibition of Human Insulin-Regulated Aminopeptidase (IRAP) by Benzopyran-Based Inhibitors

Inhibition of the insulin-regulated aminopeptidase (IRAP) improves memory and cognition in animal models. The enzyme has recently been crystallized and several series of inhibitors reported. We herein focused on one series of benzopyran-based inhibitors of IRAP known as the HFI series, with unresolved binding mode to IRAP, and developed a robust computational model to explain the structure-activity relationship (SAR) and potentially guide their further optimization. The binding model here proposed places the benzopyran ring in the catalytic binding site, coordinating the Zn²⁺ ion through the oxygen in position 3, in contrast to previous hypothesis. The whole series of HFI compounds was then systematically simulated, starting from this binding mode, using molecular dynamics and binding affinity estimated with the linear interaction energy (LIE) method. The agreement with experimental affinities supports the binding mode proposed, which was further challenged by rigorous free energy perturbation (FEP) calculations. Here, we found excellent correlation between experimental and calculated binding affinity differences, both between selected compound pairs and also for recently reported experimental data concerning the site directed mutagenesis of residue Phe544. The computationally derived structure-activity relationship of the HFI series and the understanding of the involvement of Phe544 in the binding of this scaffold provide valuable information for further lead optimization of novel IRAP inhibitors.

Lipid Dynamics in Diisobutylene-Maleic Acid (DIBMA) Lipid Particles in Presence of Sensory Rhodopsin II

Amphiphilic diisobutylene/maleic acid (DIBMA) copolymers extract lipid-encased membrane proteins from lipid bilayers in a detergent-free manner, yielding nanosized, discoidal DIBMA lipid particles (DIBMALPs). Depending on the DIBMA/lipid ratio, the size of DIBMALPs can be broadly varied which makes them suitable for the incorporation of proteins of different sizes. Here, we examine the influence of the DIBMALP sizes and the presence of protein on the dynamics of encased lipids. As shown by a set of biophysical methods, the stability of DIBMALPs remains unaffected at different DIBMA/lipid ratios. Coarse-grained molecular dynamics simulations confirm the formation of viable DIBMALPs with an overall size of up to 35 nm. Electron paramagnetic resonance spectroscopy of nitroxides located at the 5th, 12th or 16th carbon atom positions in phosphatidylcholine-based spin labels reveals that the dynamics of enclosed lipids are not altered by the DIBMALP size. The presence of the membrane protein sensory rhodopsin II from Natronomonas pharaonis (NpSRII) results in a slight increase in the lipid dynamics compared to empty DIBMALPs. The light-induced photocycle shows full functionality of DIBMALPs-embedded NpSRII and a significant effect of the protein-to-lipid ratio during preparation on the NpSRII dynamics. This study indicates a possible expansion of the applicability of the DIBMALP technology on studies of membrane protein–protein interaction and oligomerization in a constraining environment.

Exploring TEAD2 as a drug target for therapeutic intervention of cancer: A multi-computational case study

Transcriptional enhanced associate domain (TEAD) is a family of transcription factors that plays a significant role during embryonic developmental processes, and its dysregulation is responsible for tumour progression. TEAD is considered as druggable targets in various diseases, namely cancer, cardiovascular diseases and neurodegenerative disorders. Previous structural studies revealed the importance of the central hydrophobic pocket of TEAD as a potential target for small-molecule inhibitors and demonstrated flufenamic acid (FLU) (a COX-2 enzyme inhibitor) to bind and inhibit TEAD2 functions. However, to date, no drug candidates that bind specifically to TEAD2 with high selectivity and efficacy have been developed or proposed. Within this framework, we present here a case study where we have identified potential TEAD2 inhibitor candidates by integrating multiple computational approaches. Among the candidates, the top two ranked compounds ZINC95969481 (LG1) which is a fused pyrazole derivative and ZINC05203789 (LG2), a fluorene derivative resulted in much favourable binding energy scores than the reference ligand, FLU. The drug likeliness of the best compounds was also evaluated in silico to ensure the bioavailability of these compounds particularly LG1 as compared to FLU thus providing a strong rationale for their development as leads against TEAD. Molecular dynamics simulations results highlighted the role of key residues contributing to favourable interactions in TEAD2-LG1 complex with much favourable interaction and binding free energy values with respect to the reference compound. Altogether, this study provides a starting platform to be more exploited by future experimental research towards the development of inhibitors against TEAD, a persuasive strategy for therapeutic intervention in cancer treatment.

Effect of Water Microsolvation on the Excited-State Proton Transfer of 3-Hydroxyflavone Enclosed in γ-Cyclodextrin

The effect of microsolvation on excited-state proton transfer (ESPT) reaction of 3-hydroxyflavone (3HF) and its inclusion complex with γ-cyclodextrin (γ-CD) was studied using computational approaches. From molecular dynamics simulations, two possible inclusion complexes formed by the chromone ring (C-ring, Form I) and the phenyl ring (P-ring, Form II) of 3HF insertion to γ-CD were observed. Form II is likely more stable because of lower fluctuation of 3HF inside the hydrophobic cavity and lower water accessibility to the encapsulated 3HF. Next, the conformation analysis of these models in the ground (S₀) and the first excited (S₁) states was carried out by density functional theory (DFT) and time-dependent DFT (TD-DFT) calculations, respectively, to reveal the photophysical properties of 3HF influenced by the γ-CD. The results show that the intermolecular hydrogen bonding (interHB) between 3HF and γ-CD, and intramolecular hydrogen bonding (intraHB) within 3HF are strengthened in the S₁ state confirmed by the shorter interHB and intraHB distances and the red-shift of O–H vibrational modes involving in the ESPT process. The simulated absorption and emission spectra are in good agreement with the experimental data. Significantly, in the S₁ state, the keto form of 3HF is stabilized by γ-CD, explaining the increased quantum yield of keto emission of 3HF when complexing with γ-CD in the experiment. In the other word, ESPT of 3HF is more favorable in the γ-CD hydrophobic cavity than in aqueous solution.

Towards a Better Understanding of Computational Models for Predicting DNA Methylation Effects at the Molecular Level

Human DNA is a very sensitive macromolecule and slight changes in the structure of DNA can have disastrous effects on the organism. When nucleotides are modified, or changed, the resulting DNA sequence can lose its information, if it is part of a gene, or it can become a problem for replication and repair. Human cells can regulate themselves by using a process known as DNA methylation. This methylation is vitally important in cell differentiation and expression of genes. When the methylation is uncontrolled, however, or does not occur in the right place, serious pathophysiological consequences may result. Excess methylation causes changes in the conformation of the DNA double helix. The secondary structure of DNA is highly dependent upon the sequence. Therefore, if the sequence changes slightly the secondary structure can change as well. These slight changes will then cause the doublestranded DNA to be more open and available in some places where large adductions can come in and react with the DNA base pairs. Computer models have been used to simulate a variety of biological processes including protein function and binding, and there is a growing body of evidence that in silico methods can shed light on DNA methylation. Understanding the anomeric effect that contributes to the structural and conformational flexibility of furanose rings through a combination of quantum mechanical and experimental studies is critical for successful molecular dynamic simulations.

Ductile Shape-Memory Polymer Composite with Enhanced Shape Recovery Ability

In recent years, shape-memory polymers (SMPs) have received extensive attention to be used as actuators in a broad range of applications such as medical and robotic devices. Their ability to recover large deformations and their capability to be stimulated remotely have made SMPs a superior choice among different smart materials in various applications. In this study, a ductile SMP composite with enhanced shape recovery ability is synthesized and characterized. This SMP composite is made by a mixture of acrylate-based crosslinkers and monomers, as well as polystyrene (PS) with UV curing. The composite can achieve almost 100% shape recovery in 2 s by hot water or hot air. This shape recovery speed is much faster than typical acrylate-based SMPs. In addition, the composite shows excellent ductility and viscoelasticity with reduced hardness. Molecular dynamics (MD) simulations are performed for understanding the curing mechanism of this composite. With the combination of the experimental and computational works, this study paves the way in front of designing and optimizing the future SMP devices.

The Bonding Mechanism of the Micro-Interface of Polymer Coated Steel

As food and beverages require more and more green and safe packaging products, the emergence of polymer coated steel (PCS) has been promoted. PCS is a layered composite strip made of metal and polymer. To probe the bonding mechanism of PCS micro-interface, the substrate tin-free steel (TFS) was physically characterized by SEM and XPS, and cladding polyethylene terephthalate (PET) was simulated by first-principles methods of quantum mechanics (QM). We used COMPASS force field for molecular dynamics (MD) simulation. XPS pointed out that the element composition of TFS surface coating is Cr(OH)₃, Cr₂O₃ and CrO₃. The calculation results of MD and QM indicate that the chromium oxide and PET molecules compound in the form of acid-base interaction. The binding energies of Cr₂O₃ (110), (200), and (211) with PET molecules are -13.07 eV, -2.74 eV, and -2.37 eV, respectively. We established a Cr₂O₃ (200) model with different hydroxyl concentrations. It is proposed that the oxygen atom in C=O in the PET molecule combines with -OH on the surface of TFS to form a hydrogen bond. The binding energy of the PCS interface increases with the increase of the surface hydroxyl concentration of the TFS. It provides theoretical guidance and reference significance for the research on the bonding mechanism of PCS.

Multi-target approach for Alzheimer's disease treatment: computational biomolecular modeling of cholinesterase enzymes with a novel 4-N-phenylaminoquinoline derivative reveal promising potentials

The identification of dual inhibitors targeting the active sites of the cholinesterase enzymes, acetylcholinesterase (AChE) and butyrylcholinesterase (BuChE), have lately surfaced as a multi-approach towards Alzheimer treatment. More recently, a novel series of 4-N-phenylaminoquinolines was synthesized and evaluated against AChE and BuChE in which one of the compounds displayed appreciable inhibition compared to the standard compound, galantamine. To provide a clearer picture of the inhibition mechanism of this potent compound at the molecular level, computational biomolecular modeling was carried out. The investigation was initiated with the exploration of the chemical properties of the identified compound 11 b and reference drug, galantamine. Density functional theory (DFT) calculations reveal some conceptual parameters that provide information on the stability and reactivity of the compounds as potential inhibitors. To unveil the binding mechanism, energetics and enzyme-ligand interactions, molecular dynamics (MD) simulations of six different systems were executed over a period. Calculated binding free energy values are in the same order with experimental IC₅₀ data. Identification of the main residues driving optimum binding of the active compound 11 b to the binding region of both AChE and BuChE showed Trp81 and Trp110 as the most important, respectively. It was proposed that the studied compound could serve as a dual inhibitor for AChE and BuChE, therefore, would potentially be a promising moiety in a multi-target approach for the treatment of Alzheimer's disorder.Communicated by Ramaswamy H. Sarma.

Discovery of Novel Imidazopyridine GSK-3β Inhibitors Supported by Computational Approaches

The interest of research groups and pharmaceutical companies to discover novel GSK-3β inhibitors has increased over the years considering the involvement of this enzyme in many pathophysiological processes and diseases. Along this line, we recently reported on 1H-indazole-3-carboxamide (INDZ) derivatives 1-6, showing good GSK-3β inhibition activity. However, they suffered from generally poor central nervous system (CNS) permeability. Here, we describe the design, synthesis, and in vitro characterization of novel imidazo[1,5-a]pyridine-1-carboxamide (IMID 1) and imidazo[1,5-a]pyridine-3-carboxamide (IMID 2) compounds (7-18) to overcome such liability. In detail, structure-based approaches and fine-tuning of physicochemical properties guided the design of derivatives 7-18 resulting in ameliorated absorption, distribution, metabolism, and excretion (ADME) properties. A crystal structure of 16 in complex with GSK-3β enzyme (PDB entry 6Y9S) confirmed the in silico models. Despite the nanomolar inhibition activity, the new core compounds showed a reduction in potency with respect to INDZ derivatives 1-6. In this context, Molecular Dynamics (MD) and Quantum Mechanics (QM) based approaches along with NMR investigation helped to rationalize the observed structure activity relationship (SAR). With these findings, the key role of the acidic hydrogen of the central core for a tight interaction within the ATP pocket of the enzyme reflecting in good GSK-3β affinity was demonstrated.

Evolution of Angiotensin Peptides and Peptidomimetics as Angiotensin II Receptor Type 2 (AT2) Receptor Agonists

Angiotensin II receptor type 1 and 2 (AT1R and AT2R) are two G-protein coupled receptors that mediate most biological functions of the octapeptide Angiotensin II (Ang II). AT2R is upregulated upon tissue damage and its activation by selective AT2R agonists has become a promising approach in the search for new classes of pharmaceutical agents. We herein analyzed the chemical evolution of AT2R agonists starting from octapeptides, through shorter peptides and peptidomimetics to the first drug-like AT2R-selective agonist, C21, which is in Phase II clinical trials and aimed for idiopathic pulmonary fibrosis. Based on the recent crystal structures of AT1R and AT2R in complex with sarile, we identified a common binding model for a series of 11 selected AT2R agonists, consisting of peptides and peptidomimetics of different length, affinity towards AT2R and selectivity versus AT1R. Subsequent molecular dynamics simulations and free energy perturbation (FEP) calculations of binding affinities allowed the identification of the bioactive conformation and common pharmacophoric points, responsible for the key interactions with the receptor, which are maintained by the drug-like agonists. The results of this study should be helpful and facilitate the search for improved and even more potent AT2R-selective drug-like agonists.

Exploring the RNA-Recognition Mechanism Using Supervised Molecular Dynamics (SuMD) Simulations: Toward a Rational Design for Ribonucleic-Targeting Molecules?

Although proteins have represented the molecular target of choice in the development of new drug candidates, the pharmaceutical importance of ribonucleic acids has gradually been growing. The increasing availability of structural information has brought to light the existence of peculiar three-dimensional RNA arrangements, which can, contrary to initial expectations, be recognized and selectively modulated through small chemical entities or peptides. The application of classical computational methodologies, such as molecular docking, for the rational development of RNA-binding candidates is, however, complicated by the peculiarities characterizing these macromolecules, such as the marked conformational flexibility, the singular charges distribution, and the relevant role of solvent molecules. In this work, we have thus validated and extended the applicability domain of SuMD, an all-atoms molecular dynamics protocol that allows to accelerate the sampling of molecular recognition events on a nanosecond timescale, to ribonucleotide targets of pharmaceutical interest. In particular, we have proven the methodological ability by reproducing the binding mode of viral or prokaryotic ribonucleic complexes, as well as that of artificially engineered aptamers, with an impressive degree of accuracy.

Nanomechanics of few-layer materials: do individual layers slide upon folding?

Folds naturally appear on nanometrically thin materials, also called "2D materials", after exfoliation, eventually creating folded edges across the resulting flakes. We investigate the adhesion and flexural properties of single-layered and multilayered 2D materials upon folding in the present work. This is accomplished by measuring and modeling mechanical properties of folded edges, which allows for the experimental determination of the bending stiffness (κ) of multilayered 2D materials as a function of the number of layers (n). In the case of talc, we obtain κ ∝ n ³ for n ≥ 5, indicating no interlayer sliding upon folding, at least in this thickness range. In contrast, tip-enhanced Raman spectroscopy measurements on edges in folded graphene flakes, 14 layers thick, show no significant strain. This indicates that layers in graphene flakes, up to 5 nm thick, can still slip to relieve stress, showing the richness of the effect in 2D systems. The obtained interlayer adhesion energy for graphene (0.25 N/m) and talc (0.62 N/m) is in good agreement with recent experimental results and theoretical predictions. The obtained value for the adhesion energy of graphene on a silicon substrate is also in agreement with previous results.

Soyuretox, an Intrinsically Disordered Polypeptide Derived from Soybean (Glycine Max) Ubiquitous Urease with Potential Use as a Biopesticide

Ureases from different biological sources display non-ureolytic properties that contribute to plant defense, in addition to their classical enzymatic urea hydrolysis. Antifungal and entomotoxic effects were demonstrated for Jaburetox, an intrinsically disordered polypeptide derived from jack bean (Canavalia ensiformis) urease. Here we describe the properties of Soyuretox, a polypeptide derived from soybean (Glycine max) ubiquitous urease. Soyuretox was fungitoxic to Candida albicans, leading to the production of reactive oxygen species. Soyuretox further induced aggregation of Rhodnius prolixus hemocytes, indicating an interference on the insect immune response. No relevant toxicity of Soyuretox to zebrafish larvae was observed. These data suggest the presence of antifungal and entomotoxic portions of the amino acid sequences encompassing both Soyuretox and Jaburetox, despite their small sequence identity. Nuclear Magnetic Resonance (NMR) and circular dichroism (CD) spectroscopic data revealed that Soyuretox, in analogy with Jaburetox, possesses an intrinsic and largely disordered nature. Some folding is observed upon interaction of Soyuretox with sodium dodecyl sulfate (SDS) micelles, taken here as models for membranes. This observation suggests the possibility for this protein to modify its secondary structure upon interaction with the cells of the affected organisms, leading to alterations of membrane integrity. Altogether, Soyuretox can be considered a promising biopesticide for use in plant protection.

Design, synthesis, biological evaluation, and molecular dynamics of novel cholinesterase inhibitors as anti-Alzheimer's agents

A series of novel chroman-4-one derivatives were designed and synthesized successfully with good to excellent yield (3a-l). In addition, the obtained products were evaluated for their cholinesterase (ChE) inhibitory activities. The results show that among the various synthesized compounds, analogs bearing the piperidinyl ethoxy side chain with 4-hydroxybenzylidene on the 3-positions of chroman-4-one (3l) showed the most potent activity with respect to acetylcholinesterase (anti-AChE activity; IC₅₀  = 1.18 μM). In addition, the structure-activity relationship was studied and the results revealed that the electron-donating groups on the aryl ring of the 3-benzylidene fragment (3k, 3l) resulted in the designed compounds to be more potent ChE inhibitors in comparison with those having electron-withdrawing groups (3h). In this category, the strongest ChE inhibition was found for the compound containing piperidine as cyclic amine, and a hydroxyl group (for AChE, compound 3l) and fluoro group (for butyrylcholinesterase (BuChE, compound 3i) on the para-position of the aryl ring of the benzylidene group. The molecular docking and dynamics studies of the most potent compounds (3i and 3l against BuChE and AChE, respectively) demonstrated remarkable interactions with the binding pockets of the ChE enzymes and confirmed the results obtained through in vitro experiments.

Characterization, Dynamics, and Mechanism of CXCR4 Antagonists on a Constitutively Active Mutant

The G protein-coupled receptor (GPCR) CXCR4 is a co-receptor for HIV and is involved in cancers and autoimmune diseases. We characterized five purine or quinazoline core polyamine pharmacophores used for targeting CXCR4 dysregulation in diseases. All were neutral antagonists for wild-type CXCR4 and two were biased antagonists with effects on β-arrestin-2 only at high concentrations. These compounds displayed various activities for a constitutively active mutant (CAM). We use the IT1t-CXCR4 crystal structure and molecular dynamics (MD) simulations to develop two hypotheses for the activation of the N1193.35A CAM. The N1193.35A mutation facilitates increased coupling of TM helices III and VI. IT1t deactivates the CAM by disrupting the coupling between TM helices III and VI, mediated primarily by residue F872.53. Mutants of F872.53 in N1193.35A CXCR4 precluded constitutive signaling and prevented inverse agonism. This work characterizes CXCR4 ligands and provides a mechanism for N1193.35A constitutive activation.

Molecular Simulation Study on the Microscopic Structure and Mechanical Property of Defect-Containing sI Methane Hydrate

The study of changes in the related mechanical property and microscopic structure of methane hydrate during the decomposition process are of vital significance to its exploitation and comprehensive utilization. This paper had employed the molecular dynamics (MD) method to investigate the influence of defects on the microscopic structure and mechanical property of the sI methane hydrate system, and to discover the mechanical property for the defect-containing hydrate system to maintain its brittle materials. Moreover, the stress-strain curve of each system was analyzed, and it was discovered that the presence of certain defects in the methane hydrate could promote its mechanical property; however, the system mechanical property would be reduced when the defects had reached a certain degree (particle deletion rate of 9.02% in this study). Besides, the microscopic structures of the sI methane hydrate before and after failure were analyzed using the F3 order parameter value method, and it was found that the F3 order parameters near the crack would be subject to great fluctuations at the time of failure of the hydrate structure. The phenomenon and conclusions drawn in this study provide a basis for the study of the microscopic structure and mechanical characteristics of methane hydrate.

Microscopic Structural and Dynamic Features in Triphilic Room Temperature Ionic Liquids

Here we report a thorough investigation of the microscopic and mesoscopic structural organization in a series of triphilic fluorinated room temperature ionic liquids, namely [1-alkyl,3-methylimidazolium][(trifluoromethanesulfonyl)(nonafluorobutylsulfonyl)imide], with alkyl = ethyl, butyl, octyl ([C_nmim][IM₁₄], n = 2, 4, 8), based on the synergic exploitation of X-ray and Neutron Scattering and Molecular Dynamics simulations. This study reveals the strong complementarity between X-ray/neutron scattering in detecting the complex segregated morphology in these systems at mesoscopic spatial scales. The use of MD simulations delivering a very good agreement with experimental data allows us to gain a robust understanding of the segregated morphology. The structural scenario is completed with determination of dynamic properties accessing the diffusive behavior and a relaxation map is provided for [C₂mim][IM₁₄] and [C₈mim][IM₁₄], highlighting their natures as fragile glass formers.

Effective prediction model and determination of binding residues influential for inhibitors targeting HIV-1 integrase-LEDGF/p75 interface by employing solvent accessible surface area energy as key determinant

Development of a highly accurate prediction model for protein-ligand inhibition has been a major challenge in drug discovery. Herein, we describe a novel predictive model for the inhibition of HIV-1 integrase (IN)-LEDGF/p75 protein-protein interaction. The model was constructed using energy parameters approximated from molecular dynamics (MD) simulations and molecular mechanics Poisson-Boltzmann surface area (MM-PBSA) calculations. Chemometric analysis using partial least squares (PLS) regression revealed that solvent accessible surface area energy (ΔG_SASA) is the major determinant parameter contributing greatly to the prediction accuracy. PLS prediction model on the ΔG_SASA values collected from 41 complexes yielded a strong correlation between the predicted and the actual inhibitory activities (R² = 0.9666, RMSEC of pIC₅₀ values = 0.0890). Additionally, for the test set of 14 complexes, the model performed satisfactorily with very low pIC₅₀ errors (Q² = 0.5168, RMSEP = 0.3325). A strong correlation between the buried surface areas on the IN protein, when bound with IN-LEDGF/p75 inhibitors, and the respective ΔG_SASA values was also obtained. Furthermore, the current method could identify 'hot spots'of amino acid residues highly influential to the inhibitory activity prediction. This could present fruitful implications in binding site determination and future inhibitor developments targeting protein-protein interactions.Communicated by Ramaswamy H. Sarma.

Mutagenesis of α-Conotoxins for Enhancing Activity and Selectivity for Nicotinic Acetylcholine Receptors

Nicotinic acetylcholine receptors (nAChRs) are found throughout the mammalian body and have been studied extensively because of their implication in a myriad of diseases. α-Conotoxins (α-CTxs) are peptide neurotoxins found in the venom of marine snails of genus Conus. α-CTxs are potent and selective antagonists for a variety of nAChR isoforms. Over the past 40 years, α-CTxs have proven to be valuable molecular probes capable of differentiating between closely related nAChR subtypes and have contributed greatly to understanding the physiological role of nAChRs in the mammalian nervous system. Here, we review the amino acid composition and structure of several α-CTxs that selectively target nAChR isoforms and explore strategies and outcomes for introducing mutations in native α-CTxs to direct selectivity and enhance binding affinity for specific nAChRs. This review will focus on structure-activity relationship studies involving native α-CTxs that have been rationally mutated and molecular interactions that underlie binding between ligand and nAChR isoform.

Insights into the role of d-amino acid oxidase mutations in amyotrophic lateral sclerosis

Missense mutations in the coding region of d-amino acid oxidase (DAO) have been found in patients suffering from amyotrophic lateral sclerosis (ALS). Mutations primarily impair the enzymatic activity of DAO and cause neurodegeneration due to an abnormal accumulation of d-serine in the spinal cord. However, the structural and dynamic changes that lead to impaired enzymatic activity are not fully understood. We present here extensive molecular dynamics simulations of wild-type, and all reported ALS-associated DAO mutants to elucidate the plausible mechanisms of impaired enzymatic activity, a critical function needed for neuroprotection. Simulation results show that DAO mutations disrupt several key interactions with the active site residues and decrease the conformational flexibility of active site loop comprising 216 to 228 residues, necessary for substrate binding and product release. This conformational restriction of the active site loop in the mutants is mainly due to the distortion of critical salt bridge and hydrogen bond interactions compared with wild-type. Furthermore, binding free energy calculations show that DAO mutants have a lower binding affinity toward cofactor flavin adenine dinucleotide and substrate imino-serine than the wild-type. A closer look at the cofactor and substrate interaction profiles further show that DAO mutants have lost several critical interactions with the neighboring residues as compared with wild-type. Taken together, this study provides first-hand explanation of crucial structural features that lead to the loss of enzymatic function in DAO mutants and highlights the need of further genomic scans of patients with ALS to map the association of novel DAO variants in ALS pathophysiology.

Structural insights into the aggregation mechanism of huntingtin exon 1 protein fragment with different polyQ-lengths

Huntington disease is a neurodegenerative disorder caused by the expansion of polyglutamine (polyQ) at the N-terminal of the huntingtin exon 1 protein. The detailed structure and the mechanism behind this aggregation remain unclear and it is assumed that the polyQ undergoes a conformational transition to the β-sheet structure when it aggregates. Investigating the misfolding of polyQ facilitates the determination of the molecular mechanism of aggregation and can potentially help in developing a novel approach to inhibit polyQ aggregation. Moreover, the flanking sequences of the polyQ region play a vital role in structural changes and the aggregation mechanism. We performed all-atom molecular dynamics simulations to gain structural insights into the aggregation mechanism using eight different models with glutamine repeat lengths Q₂₇ , Q₂₇ P₁₁ , Q₃₄ , Q₃₅ , Q₃₆ , Q₄₀ , Q₅₀ , and Q₅₀ P₁₁ . In the models without flanking polyPs, we noticed that the transformation of a random coil to β-sheet occurs when the number of Q increases. We also found that the flanking polyPs prevent aggregation by decreasing the probability of forming a β-sheet structure. When polyQ length increases, the 17 N-terminal flanking residues are more likely to adopt a β-sheet conformation from α-helix and coil. From our simulations, we suggest that at least 34 glutamines are required for initiating aggregation and 40 residues length is critical for the aggregation of huntingtin exon 1 protein for disease onset. This study provides structural insights into misfolding and the role of flanking sequences in huntingtin aggregation which will further help in developing therapeutic strategies for Huntington's disease.

Molecular Basis of Mammalian Odor Discrimination: A Status Report

Humans have 396 unique, intact olfactory receptors (ORs), G-protein coupled receptors (GPCRs) containing receptor-specific binding sites; other mammals have more. Activation of these transmembrane proteins by an odorant initiates a signaling cascade, evoking an action potential leading to perception of a smell. Because the number of distinguishable odorants vastly exceeds the number of ORs, research has focused on mechanisms of recognition and signaling processes for classes of odorants. In this review, selected recent examples will be presented of "deorphaned" mammalian receptors, where the OR ligands (odorants) as well as key aspects of receptor-odorant interactions were identified using odorant-mediated receptor activation data together with site-directed mutagenesis and molecular modeling. Based on cumulative evidence from OR deorphaning and olfactory receptor neuron activation studies, a receptor-ligand docking model rather than an alternative bond vibration model is suggested to best explain the molecular basis of the exquisitely sensitive odor discrimination in mammals.

The Hypervariable Loops of Free TCRs Sample Multiple Distinct Metastable Conformations in Solution

CD4⁺ and CD8⁺ αβ T cell antigen recognition is determined by the interaction between the TCR Complementarity Determining Region (CDR) loops and the peptide-presenting MHC complex. These T cells are known for their ability to recognize multiple pMHC complexes, and for a necessary promiscuity that is required for their selection and function in the periphery. Crystallographic studies have previously elucidated the role of structural interactions in TCR engagement, but our understanding of the dynamic process that occurs during TCR binding is limited. To better understand the dynamic states that exist for TCR CDR loops in solution, and how this relates to their states when in complex with pMHC, we simulated the 2C T cell receptor in solution using all-atom molecular dynamics in explicit water and constructed a Markov State Model for each of the CDR3α and CDR3β loops. These models reveal multiple metastable states for the CDR3 loops in solution. Simulation data and metastable states reproduce known CDR3β crystal conformations, and reveal several novel conformations suggesting that CDR3β bound states are the result of search processes from nearby pre-existing equilibrium conformational states. Similar simulations of the invariant, Type I Natural Killer T cell receptor NKT15, which engages the monomorphic, MHC-like CD1d ligand, demonstrate that iNKT TCRs also have distinct states, but comparatively restricted degrees of motion.

Computational Studies on the Inhibitor Selectivity of Human JAMM Deubiquitinylases Rpn11 and CSN5

Deubiquitinylases (DUBs) are highly specialized enzymes which are responsible for removal of covalently attached ubiquitin(s) from the targeted proteins. DUBs play an important role in maintaining the protein homeodynamics. Recently, DUBs have emerged as novel therapeutic targets in cancer, inflammation, diabetes, and neurodegeneration. Among the different families of DUBs, the metalloprotease group or JAB1/MOV34/MPR1 (JAMMs) proteases are unique in terms of catalytic mechanism. JAMMs exhibit a Zn²⁺-dependent deubiquitinylase activity. Within the JAMM family, deubiquitinylases Rpn11 and CSN5 are constituents of large bimolecular complexes, namely the 26S proteasome and COP9 signalosome (CSN), respectively. Rpn11 and CSN5 are potential drug targets in cancer and selective inhibitors of both proteins have been reported in the literature. However, the selectivity of JAMM inhibitors (capzimin for RPN11 and CSN5i-3 for CSN5) has not been structurally resolved yet. In the present work, we have explored the binding modes of capzimin and CSN5i-3 and rationalize their selectivity for Rpn11 and CSN5 targets. We found that capzimin interacts with the active site Zn⁺² of Rpn11 in a bidentate manner and also interacts with the residues in the distal ubiquitin binding site. MD simulations studies and binding energy analysis revealed that the selective binding of the inhibitors can be only explained by the consideration of larger heterodimeric complexes of Rpn11 (Rpn8-Rpn11) and CSN5 (CSN5-CSN6). Simulation of these protein-protein complexes is necessary to avoid unrealistic large conformational changes. The selective binding of inhibitors is mainly governed by residues in the distal ubiquitin binding site. This study demonstrates that selective inhibitor binding design for Rpn11 and CSN5 JAMM proteases requires consideration of heterodimeric protein-protein target structures.

Exploring Peptide⁻Solvent Interactions: A Computational Study

The dilemma of reconciling the contradictory evidence regarding the conformation of long solvated peptide chains is the so-called "reconciliation problem". Clues regarding the stability of certain conformations likely lie in the electronic structure at the peptide⁻solvent interface, but the peptide⁻solvent interaction is not fully understood. Here, we study the influence of aqueous solvent on peptide conformations by using classical molecular dynamics (MD) and quantum mechanical/molecular mechanical (QM/MM) energy calculations. The model systems include an 11-residue peptide, X 2 A 7 O 2 (XAO), where X, A, and O denote diaminobutyric acid, alanine, and ornithine, respectively, and a 9-mer (Arg-Pro-Pro-Gly-Phe-Ser-Ala-Phe-Lys). Spectroscopic and MD data present conflicting evidence regarding the structure of XAO in water; some results indicate that XAO adopts a polyproline II (P II ) conformation, whereas other findings suggest that XAO explores a range of conformations. To investigate this contradiction, we present here the results of MD simulations of XAO and the 9-mer in aqueous solution, combined with QM/MM energy calculations.

Structure, Function, and Modulation of γ-Aminobutyric Acid Transporter 1 (GAT1) in Neurological Disorders: A Pharmacoinformatic Prospective

γ-Aminobutyric acid (GABA) Transporters (GATs) belong to sodium and chloride dependent-transporter family and are widely expressed throughout the brain. Notably, GAT1 is accountable for sustaining 75% of the synaptic GABA concentration and entails its transport to the GABAA receptors to initiate the receptor-mediated inhibition of post-synaptic neurons. Imbalance in ion homeostasis has been associated with several neurological disorders related to the GABAergic system. However, inhibition of the GABA uptake by these transporters has been accepted as an effective approach to enhance GABAergic inhibitory neurotransmission in the treatment of seizures in epileptic and other neurological disorders. Here, we reviewed computational methodologies including molecular modeling, docking, and molecular dynamic simulations studies to underscore the structure and function of GAT1 in the GABAergic system. Additionally, various SAR and QSAR methodologies have been reviewed to probe the 3D structural features of inhibitors required to modulate GATs activity. Overall, present review provides an overview of crucial role of GAT1 in GABAergic system and its modulation to evade neurological disorders.

Dynamic perspectives into the mechanisms of mutation-induced p53-DNA binding loss and inactivation using active perturbation theory: Structural and molecular insights toward the design of potent reactivators in cancer therapy

The DNA-binding ability of p53 represents the crux of its tumor suppressive activities, which involves transcriptional activation of target genes responsible for apoptosis and cell-cycle arrest. Mutational occurrences within or in close proximity to the DNA-binding surface of p53 have accounted for the loss of direct DNA-binding ability and inactivation implicated in many cases of cancer. Moreover, the design of therapeutic compounds that can restore DNA-binding ability in p53 mutants has been identified as a way forward in curtailing their oncogenic activities. However, there is still the need for more insights into evaluate the perturbations that occur at the DNA-binding interface of mp53 relative to DNA-binding loss, inactivation, and design of potent reactivators, hence the purpose of this study. Therefore, we evaluated p53-structural (R175H) and contact (R273C) mutational effects using tunnel perturbation analysis and other computational tools. We identified significant perturbations in the active tunnels of p53, which resulted in altered geometry and loss, unlike in the wild-type p53. This corroborated with structural, DNA-binding, and interaction network analysis, which showed that loss of flexibility, repulsion of DNA-interactive residues, and instability occurred at the binding interface of both mutants. Also, these mutations altered bonding interactions and network topology at the DNA-binding interface, resulting in the reduction of p53-DNA binding proximity and affinity. Therefore, these findings would aid the structure-based design of novel chemical entities capable of restoring p53-DNA binding and activation.

Thinking outside the Laboratory: Analyses of Antibody Structure and Dynamics within Different Solvent Environments in Molecular Dynamics (MD) Simulations

Monoclonal antibodies (mAbs) have revolutionized the biomedical field, directly influencing therapeutics and diagnostics in the biopharmaceutical industry, while continuing advances in computational efficiency have enabled molecular dynamics (MD) simulations to provide atomistic insight into the structure and function of mAbs. Despite the success of MD tools, further optimizations are still required to enhance the computational efficiency of complex mAb simulations. This issue can be tackled by changing the way the solvent system is modelled to reduce the number of atoms to be tracked but must be done without compromising the accuracy of the simulations. In this work, the structure of the IgG_2a antibody was analyzed in three solvent systems: explicit water and ions, implicit water and ions, and implicit water and explicit ions. Root-mean-square distance (RMSD), root-mean-square fluctuations (RMSF), and interchain angles were used to quantify structural changes. The explicit system provides the most atomistic detail but is ~6 times slower in its exploration of configurational space and required ~4 times more computational time on our supercomputer than the implicit simulations. Overall, the behavior of the implicit and explicit simulations is quantifiably similar, with the inclusion of explicit ions in the implicit simulation stabilizing the antibody to reproduce well the statistical fluctuations of the fully explicit system. Therefore, this approach holds promise to maximize the use of computational resources to explore antibody behavior.

DL_ANALYSER Notation for Atomic Interactions (DANAI): A Natural Annotation System for Molecular Interactions, Using Ethanoic Acid Liquid as a Test Case

The DL_ANALYSER Notation for Atomic Interactions, DANAI, is the notation syntax to describe interactions between molecules. This notation can annotate precisely the detailed atomistic interactions without having to resolve to diagrammatic illustrations, and yet can be interpreted easily by both human users and computational means. By making use of the DL_F Notation, a universal atom typing scheme for molecular simulations, DANAI contains the expression of atomic species in a natural chemical sense. It is implemented within DL_ANALYSER, a general analysis software program for DL_POLY molecular dynamics simulation software. By making references to the molecular dynamics simulations of pure ethanoic acid liquid, it is shown that DL_ANALYSER can identify and distinguish a variety of hydrogen bond and hydrophobic contact networks through the use of the DANAI expression. It was found that the carboxylic groups preferentially orientated in a "head-to-tail" conformation to form hydrogen bonds between the carbonyl oxygen and hydroxyl hydrogen, resulting in a series of linear structures that intertwined with pockets of methyl clusters.

Synthesis and preliminary structure-activity relationship study of 2-aryl-2H-pyrazolo[4,3-c]quinolin-3-ones as potential checkpoint kinase 1 (Chk1) inhibitors

The serine-threonine checkpoint kinase 1 (Chk1) plays a critical role in the cell cycle arrest in response to DNA damage. In the last decade, Chk1 inhibitors have emerged as a novel therapeutic strategy to potentiate the anti-tumour efficacy of cytotoxic chemotherapeutic agents. In the search for new Chk1 inhibitors, a congeneric series of 2-aryl-2 H-pyrazolo[4,3-c]quinolin-3-one (PQ) was evaluated by in-vitro and in-silico approaches for the first time. A total of 30 PQ structures were synthesised in good to excellent yields using conventional or microwave heating, highlighting that 14 of them are new chemical entities. Noteworthy, in this preliminary study two compounds 4e₂ and 4h₂ have shown a modest but significant reduction in the basal activity of the Chk1 kinase. Starting from these preliminary results, we have designed the second generation of analogous in this class and further studies are in progress in our laboratories.

Cluster Formation of Polyphilic Molecules Solvated in a DPPC Bilayer

We analyse the initial stages of cluster formation of polyphilic additive molecules which are solvated in a dipalmitoylphosphatidylcholine (DPPC) lipid bilayer. Our polyphilic molecules comprise an aromatic (trans-bilayer) core domain with (out-of-bilayer) glycerol terminations, complemented with a fluorophilic and an alkyl side chain, both of which are confined within the aliphatic segment of the bilayer. Large-scale molecular dynamics simulations (1 μ s total duration) of a set of six of such polyphilic additives reveal the initial steps towards supramolecular aggregation induced by the specific philicity properties of the molecules. For our intermediate system size of six polyphiles, the transient but recurrent formation of a trimer is observed on a characteristic timescale of about 100 ns. The alkane/perfluoroalkane side chains show a very distinct conformational distribution inside the bilayer thanks to their different philicity, despite their identical anchoring in the trans-bilayer segment of the polyphile. The diffusive mobility of the polyphilic additives is about the same as that of the surrounding lipids, although it crosses both bilayer leaflets and tends to self-associate.

Investigation on the binding mechanism of loratinib with the c-ros oncogene 1 (ROS1) receptor tyrosine kinase via molecular dynamics simulation and binding free energy calculations

The c-ros oncogene 1 (ROS1) has proven to be an important cancer target for the treatment of various human cancers. The anaplastic lymphoma kinase inhibitor crizotinib has been granted approval for the treatment of patients with ROS1 positive metastatic non-small-cell lung cancer by the Food and Drug Administration on 2016. However, serious resistance due to the secondary mutation of glycine 2032 to arginine (G2032R) was developed in clinical studies. Loratinib (PF-06463922), a macrocyclic analog of crizotinib, showed significantly improved inhibitory activity against wild-type (WT) ROS1 and ROS1^G2032R mutant. To provide insights into the inhibition mechanism, molecular dynamics simulations and free energy calculations were carried out for the complexes of loratinib with WT and G2032R mutated ROS1. The apo-ROS1^WT and apo-ROS1^G2032R systems showed similar RMSF distributions, while ROS1^G2032R-loratinib showed significantly higher than that of WT ROS1-loratinib, which revealed that the binding of loratinib to ROS1^G2032R significantly interfered the fluctuation of protein. Calculations of binding free energies indicate that G2032R mutation significantly reduces the binding affinity of loratinib for ROS1, which arose mostly from the increase of conformation entropy and the decrease of solvation energy. Furthermore, detailed per-residue binding free energies highlighted the increased and decreased contributions of some residues in the G2032R mutated systems. The present study revealed the detailed inhibitory mechanism of loratinib as potent WT and G2032R mutated ROS1 inhibitor, which was expected to provide a basis for rational drug design.