Effects of thermostats/barostats on physical properties of liquids by molecular dynamics simulations

Structure and Ligand Based Virtual Screening and MPO Topological Analysis of Triazolo Thiadiazepine-fused Coumarin Derivatives as Anti-Parkinson Drug Candidates

Parkinson's disease (PD) is a debilitating condition that can cause locomotor problems in affected patients, such as tremors and body rigidity. PD therapy often includes the use of monoamine oxidase B (MAOB) inhibitors, particularly phenylhalogen compounds and coumarin-based semi-synthetic compounds. The objective of this study was to analyze the structural, pharmacokinetic, and pharmacodynamic profile of a series of Triazolo Thiadiazepine-fused Coumarin Derivatives (TDCDs) against MAOB, in comparison with the inhibitor safinamide. To achieve this goal, we utilized structure-based virtual screening techniques, including target prediction and absorption, distribution, metabolism, and excretion (ADME) prediction based on multi-parameter optimization (MPO) topological analysis, as well as ligand-based virtual screening techniques, such as docking and molecular dynamics. The findings indicate that the TDCDs exhibit structural similarity to other bioactive compounds containing coumarin and MAOB-binding azoles, which are present in the ChEMBL database. The topological analyses suggest that TDCD3 has the best ADME profile, particularly due to the alignment between low lipophilicity and high polarity. The coumarin and triazole portions make a strong contribution to this profile, resulting in a permeability with Papp estimated at 2.15 × 10-5 cm/s, indicating high cell viability. The substance is predicted to be metabolically stable. It is important to note that this is an objective evaluation based on the available data. Molecular docking simulations showed that the ligand has an affinity energy of - 8.075 kcal/mol with MAOB and interacts with biological substrate residues such as Pro102 and Phe103. The results suggest that the compound has a safe profile in relation to the MAOB model, making it a promising active ingredient for the treatment of PD.

Multi-targeted therapeutic potential of stigmasterol from the Euphorbia ammak plant in treating lung and breast cancer

Cancer is the most prevalent disease globally, which presents a significant challenge to the healthcare industry, with breast and lung cancer being predominant malignancies. This study used RNA-seq data from the TCGA database to identify potential biomarkers for lung and breast cancer. Tumor Necrosis Factor (TNFAIP8) and Sulfite Oxidase (SUOX) showed significant expression variation and were selected for further study using structure-based drug discovery (SBDD). Compounds derived from the Euphorbia ammak plant were selected for in-silico study with both TNFAIP8 and SUOX. Stigmasterol had the greatest binding scores (normalized scores of -8.53 kcal/mol and -9.69 kcal/mol) with both proteins, indicating strong stability in their binding pockets throughout the molecular dynamics' simulation. Although Stigmasterol first changed its initial conformation (RMSD = 0.5 nm with the starting conformation) in SUOX, it eventually reached a stable conformation (RMSD of 1.5 nm). The compound on TNFAIP8 showed a persistent shape (RMSD of 0.35 nm), indicating strong protein stability. The binding free energy of the complex was calculated using the MM/GBSA technique; TNFAIP8 had a ΔGTOTAL of -24.98 kcal/mol, with TYR160 being the most significant residue, contributing -2.52 kcal/mol. On the other hand, the SUOX complex had a binding free energy of -16.87 kcal/mol, with LEU151 being the primary contributor (-1.17 kcal/mol). Analysis of the complexes' free energy landscape unveiled several states with minimum free energy, indicating robust interactions between the protein and ligand. In its conclusion, this work emphasises the favourable ability of Stigmasterol to bind with prospective targets for lung and breast cancer, indicating the need for more experimental study.

Effect of temperature on anisotropic bending elasticity of dsRNA: an all-atom molecular dynamics simulation

Employing all-atom molecular dynamics simulations, we examined the temperature-dependent behavior of bending elasticity in double-stranded RNA (dsRNA). Specifically, we focused on the bending persistence length and its constituent components, namely, the tilt and roll stiffness. Our results revealed a near-linear decrease in these stiffness components as a function of temperature, thereby highlighting the increased flexibility of dsRNA at elevated temperatures. Furthermore, our data revealed a significant anisotropy in dsRNA bending elasticity, which diminished with increasing temperature, attributable to marked disparities in tilt and roll stiffness components. We delineated the underlying biophysical mechanisms and corroborated our findings with extant literature. These observations offer salient implications for advancing our understanding of nucleic acid elasticity, and are pertinent to potential medical applications.

Improved microalgae carbon fixation and microplastic sedimentation in the lake through in silico method

The impact of microplastics in lake water environments on microalgae carbon fixation and microplastic sedimentation has attracted global attention. The molecular dynamic simulation method was used to design microplastic additive proportioning schemes for improving microalgae carbon fixation and microplastic sedimentation. Results showed that the harm of microplastics can be effectively alleviated by adjusting the proportioning scheme of plastic additives. Besides, the decabromodiphenyl oxide (DBDPO) was identified as the main additive that affect the microalgae carbon fixation and microplastic sedimentation. Thus, a molecular modification based on CiteSpace visual analysis was firstly used and 12 DBDPO derivatives were designed. After the screening, DBDPO-2 and DBDPO-5 became the environmentally friendly DBDPO alternatives, with the highest microalgae carbon fixation and microplastic sedimentation ability enhancement of over 25 %. Compared to DBDPO, DBDPO derivatives were found easier to stimulate the adsorption and binding ability of surrounding hotspot amino acids to CO2 and ribulose-5-phosphate, increasing the solvent-accessible surface area of microplastics, thus improving the microalgae carbon fixation and microplastic sedimentation ability. This study provides theoretical support for simultaneously promoting the microalgae carbon fixation and microplastic sedimentation in the lake water environment and provides scientific basis for the protection and sustainable development of lake water ecosystem.

Immunoinformatics design of a structural proteins driven multi-epitope candidate vaccine against different SARS-CoV-2 variants based on fynomer

The ideal vaccines for combating diseases that may emerge in the future require more than simply inactivating a few pathogenic strains. This study aims to provide a peptide-based multi-epitope vaccine effective against various severe acute respiratory syndrome coronavirus 2 strains. To design the vaccine, a library of peptides from the spike, nucleocapsid, membrane, and envelope structural proteins of various strains was prepared. Then, the final vaccine structure was optimized using the fully protected epitopes and the fynomer scaffold. Using bioinformatics tools, the antigenicity, allergenicity, toxicity, physicochemical properties, population coverage, and secondary and three-dimensional structures of the vaccine candidate were evaluated. The bioinformatic analyses confirmed the high quality of the vaccine. According to further investigations, this structure is similar to native protein and there is a stable and strong interaction between vaccine and receptors. Based on molecular dynamics simulation, structural compactness and stability in binding were also observed. In addition, the immune simulation showed that the vaccine can stimulate immune responses similar to real conditions. Finally, codon optimization and in silico cloning confirmed efficient expression in Escherichia coli. In conclusion, the fynomer-based vaccine can be considered as a new style in designing and updating vaccines to protect against coronavirus disease.

SARS-CoV-2 omicron RBD forms a weaker binding affinity to hACE2 compared to Delta RBD in in-silico studies

The COVID-19 pandemic sparked an unprecedented race in biotechnology in a search for effective therapies and a preventive vaccine. The continued appearance of SARS-CoV-2 variants of concern (VoCs) further swept the world. The entry of SARS-CoV-2 into cells is mediated by binding the receptor-binding domain (RBD) of the S protein to the cell-surface receptor, human angiotensin-converting enzyme 2 (hACE2). In this study, using a coarse-grained force field to parameterize the system, we employed steered-molecular dynamics (SMD) simulations to reveal the binding of SARS-CoV-2 Delta/Omicron RBD to hACE2. Our benchmarked results demonstrate a good correlation between computed rupture force and experimental binding free energy for known protein-protein systems. Moreover, our findings show that the Omicron RBD has a weaker binding affinity to hACE2, consistent with the respective experimental results. This indicates that our method can effectively be applied to other emerging SARS-CoV-2 strains.Communicated by Ramaswamy H. Sarma.

Dissecting the CRISPR Cas1-Cas2 Protospacer Binding and Selection Mechanism by Using Molecular Dynamics Simulations

Cas1 and Cas2 are highly conserved proteins among the clustered regularly interspaced short palindromic repeat Cas (CRISPR-Cas) systems and play a crucial role in protospacer selection and integration. According to the double-forked CRISPR Cas1-Cas2 complex, we conducted extensive all-atom molecular dynamics simulations to investigate the protospacer DNA binding and recognition. Our findings revealed that single-point amino acid mutations in Cas1 or in Cas2 had little impact on the binding of the protospacer, both in the binding and precatalytic states. In contrast, multiple-point amino acid mutations, particularly G74A, P80L, and V89A mutations on Cas2 and Cas2' proteins (m-multiple1 system), significantly affected the protospacer binding and selection. Notably, mutations on Cas2 and Cas2' led to an increased number of hydrogen bonds (#HBs) between Cas2&Cas2' and the dsDNA in the m-multiple1 system compared with the wild-type system. And the strong electrostatic interactions between Cas1-Cas2 and the protospacer DNA (psDNA) in the m-multiple1 system again suggested the increase in the binding affinity of protospacer acquisition. Specifically, mutations in Cas2 and Cas2' can remotely make the protospacer adjacent motif complementary (PAMc) sequences better in recognition by the two active sites, while multiple mutations K211E, P202Q, P212L, R138L, V134A, A286T, P282H, and P294H on Cas1a/Cas1b&Cas1a'/Cas1b' (m-multiple2 system) decrease the #HBs and the electrostatic interactions and make the PAMc worse in recognition compared with the wild-type system.

Integrated Computational Pipeline for the High-Throughput Discovery of Cell Adhesion Peptides

Cell adhesion peptides (CAPs) often play a critical role in tissue engineering research. However, the discovery of novel CAPs for diverse applications remains a challenging and time-intensive process. This study presents an efficient computational pipeline integrating sequence embeddings, binding predictors, and molecular dynamics simulations to expedite the discovery of new CAPs. A Pro2vec model, trained on vast CAP data sets, was built to identify RGD-similar tripeptide candidates. These candidates were further evaluated for their binding affinity with integrin receptors using the Mutabind2 machine learning model. Additionally, molecular dynamics simulations were applied to model receptor-peptide interactions and calculate their binding free energies, providing a quantitative assessment of the binding strength for further screening. The resulting peptide demonstrated performance comparable to that of RGD in endothelial cell adhesion and spreading experimental assays, validating the efficacy of the integrated computational pipeline.

Abatement of the binding of human hexokinase II enzyme monomers by in-silico method with the design of inhibitory peptides

The hexokinase II enzyme is bound to the (VDAC1) channel in the form of a dimer and prevents the release of cell death factors from mitochondria to the cytoplasm. Studies have shown that blocking the binding of hexokinase II enzyme to (VDAC1) led to the initiation of apoptosis in cancer cells. No peptide has been designed so far to inhibit hexokinase II. The aim of this study was to inhibit the dimerization of enzyme subunits in order to inhibition the formation of (VDAC1) and the hexokinase II complex. In this study, the molecular dynamics simulation of the enzyme in monomer and dimer states was investigated in terms of RMSF, RMSD and radius of gyration. The following process involves extracting and designing variable-length peptides from the interacting segments of enzyme monomers. Using molecular dynamics simulation, the stability of the peptide was determined in terms of RMSD. Molecular docking was used to investigate the interaction between the designed peptides. Finally, the inhibitory effect of peptides on subunit association was measured using dynamic light scattering (DLS) technique. Our results showed that the designed peptides, which mimic common amino acids in dimerization, interrupt the bona fide form of the enzyme subunits. The result of this study provides a new way to disrupt the assembly process and thereby decreased the function of the hexokinase II.

Supplementary Information

The online version contains supplementary material available at 10.1007/s40203-024-00201-8.

Liquid-Vapor Coexistence and Spontaneous Evaporation at Atmospheric Pressure of Common Rigid Three-Point Water Models in Molecular Simulations

Molecular dynamics (MD) simulations are widely used to investigate molecular systems at atomic resolution including biomolecular structures, drug-receptor interactions, and novel materials. Frequently, MD simulations are performed in an aqueous solution with explicit models of water molecules. Commonly, such models are parameterized to reproduce the liquid phase of water under ambient conditions. However, often, simulations at significantly higher temperatures are also of interest. Hence, it is important to investigate the equilibrium of the liquid and vapor phases of molecular models of water at elevated temperatures. Here, we evaluate the behavior of 11 common rigid three-point water models over a wide range of temperatures. From liquid-vapor coexistence simulations, we estimated the critical points and studied the spontaneous evaporation of these water models. Moreover, we investigated the influence of the system size, choice of the pressure-coupling algorithm, and rate of heating on the process and compared them with the experimental data. We found that modern rigid three-point water models reproduce the critical point surprisingly well. Furthermore, we discovered that the critical temperature correlates with the quadrupole moment of the respective water model. This indicates that the spatial arrangement of the partial charges is important for reproducing the liquid-vapor phase transition. Our findings may guide the selection of water models for simulations conducted at high temperatures.

Influence of temperature on bend, twist and twist-bend coupling of dsDNA

The temperature-dependent bend and twist elasticities of dsDNA, as well as their couplings, were explored through all-atom molecular dynamics simulations. Three rotational parameters, tilt, roll, and twist, were employed to assess the bend and twist elasticities through their stiffness matrix. Our analysis indicates that the bend and twist stiffnesses decrease as the temperature rises, primarily owing to entropic influences stemming from thermodynamic fluctuations. Furthermore, the couplings between these rotational parameters also exhibit a decline with increasing temperature, although the roll-twist coupling displays greater strength than the tilt-roll and tilt-twist couplings, attributed to its more robust correction component. We elucidated the influence of temperature on bend and twist elasticities based on the comparisons between various models and existing data.

Inhibition of polymorphic MexXY-OprM efflux system in Pseudomonas aeruginosa clinical isolates by Berberine derivatives

The MexXY-OprM multidrug efflux pump (EP) in aminoglycosides resistant Pseudomonas aeruginosa is one of the major resistance mechanisms, which is often overexpressed in strains isolated from pulmonary chronic disease such as cystic fibrosis.[1-3] In this research, we focused on the design of potential efflux pumps inhibitors, targeting MexY, the inner membrane component, in an allosteric site. Berberine[4] has been considered as lead molecule since we previously demonstrated its effectiveness in targeting MexY in laboratory reference strains.[5,6] Since this protein is often present in polymorphic variants in clinical strains, we sequenced and modeled all the mutated forms and we synthesized and evaluated by computational techniques, some berberine derivatives carrying an aromatic functionalization in its 13-C ring position. These compounds were tested in vitro against clinical P. aeruginosa strains for antimicrobial and antibiofilm activity. In conclusion, the results demonstrated the importance of the aromatic moiety functionalization in exerting the EP inhibitory activity in synergy with the aminoglycoside tobramycin. More, we found that aminoacidic composition of MexY in different strains must be considered for predicting potential binding site and affects the different activity of berberine derivatives. Finally, the antibiofilm effect of these new EPIs is promising, particularly for o-CH3-berberine derivative.

Understanding a point mutation signature D54K in the caspase activation recruitment domain of NOD1 capitulating concerted immunity via atomistic simulation

Point mutation D54K in the human N-terminal caspase recruitment domain (CARD) of nucleotide-binding oligomerization domain -1 (NOD1) abrogates an imperative downstream interaction with receptor-interacting protein kinase (RIPK2) that entails combating bacterial infections and inflammatory dysfunction. Here, we addressed the molecular details concerning conformational changes and interaction patterns (monomeric-dimeric states) of D54K by signature-based molecular dynamics simulation. Initially, the sequence analysis prioritized D54K as a pathogenic mutation, among other variants, based on a sequence signature. Since the mutation is highly conserved, we derived the distant ortholog to predict the sequence and structural similarity between native and mutant. This analysis showed the utility of 33 communal core residues associated with structural-functional preservation and variations, concurrently served to infer the cryptic hotspots Cys39, Glu53, Asp54, Glu56, Ile57, Leu74, and Lys78 determining the inter helical fold forming homodimers for putative receptor interaction. Subsequently, the atomistic simulations with free energy (MM/PB(GB)SA) calculations predicted structural alteration that takes place in the N-terminal mutant CARD where coils changed to helices (45 α3- L4-α4-L6- α683) in contrast to native (45T2-L4-α4-L6-T483). Likewise, the C-terminal helices 93T1-α7105 connected to the loops distorted compared to native 93α6-L7105 may result in conformational misfolding that promotes functional regulation and activation. These structural perturbations of D54K possibly destabilize the flexible adaptation of critical homotypic NOD1CARD-CARDRIPK2 interactions (α4Asp42-Arg488α5 and α6Phe86-Lys471α4) is consistent with earlier experimental reports. Altogether, our findings unveil the conformational plasticity of mutation-dependent immunomodulatory response and may aid in functional validation exploring clinical investigation on CARD-regulated immunotherapies to prevent systemic infection and inflammation.Communicated by Ramaswamy H. Sarma.

Molecular dynamics investigation on synthesis of a pH- and temperature-sensitive carbon nanotube loaded with doxorubicin

The many exotic properties of carbon nanotubes (CNTs) make them a powerful attraction in the field of drug delivery systems (DDS). In this work, based on quantum chemical calculation and molecular simulation techniques, polyacrylic acid (PAA) and N-isopropyl acrylamide (NIP) are selected and acted simultaneously on the CNT to form a stable system (FCNT). As a potential DDS, FCNT captures the dispersed doxorubicin (DOX) molecules around it and maintains a stable configuration. In these processes, electrostatic and van der Waals forces act synergistically, with van der Waals forces dominating. Compared to NIP, PAA molecules exhibit stronger adhesion and encapsulation efficiency to CNT and stronger adsorption capacity to DOX. This study reveals the mechanism of action among PAA, NIP, CNT, and DOX, providing feasibility verification and prospective guidance for the experimental synthesis of PAA-NIP-CNT-type multifunctional DDS, and also broadening the idea for exploring more efficient DDS suitable for DOX.

Computer-Aided Strategy on 5-(Substituted benzylidene) Thiazolidine-2,4-Diones to Develop New and Potent PTP1B Inhibitors: QSAR Modeling, Molecular Docking, Molecular Dynamics, PASS Predictions, and DFT Investigations

A set of 5-(substituted benzylidene) thiazolidine-2,4-dione derivatives was explored to study the main structural requirement for the design of protein tyrosine phosphatase 1B (PTP1B) inhibitors. Utilizing multiple linear regression (MLR) analysis, we constructed a robust quantitative structure-activity relationship (QSAR) model to predict inhibitory activity, resulting in a noteworthy correlation coefficient (R2) of 0.942. Rigorous cross-validation using the leave-one-out (LOO) technique and statistical parameter calculations affirmed the model's reliability, with the QSAR analysis revealing 10 distinct structural patterns influencing PTP1B inhibitory activity. Compound 7e(ref) emerged as the optimal scaffold for drug design. Seven new PTP1B inhibitors were designed based on the QSAR model, followed by molecular docking studies to predict interactions and identify structural features. Pharmacokinetics properties were assessed through drug-likeness and ADMET studies. After that density functional theory (DFT) was conducted to assess the stability and reactivity of potential diabetes mellitus drug candidates. The subsequent dynamic simulation phase provided additional insights into stability and interactions dynamics of the top-ranked compound 11c. This comprehensive approach enhances our understanding of potential drug candidates for treating diabetes mellitus.

Peptide ligands targeting the vesicular stomatitis virus G (VSV-G) protein for the affinity purification of lentivirus particles

The recent uptick in the approval of ex vivo cell therapies highlights the relevance of lentivirus (LV) as an enabling viral vector of modern medicine. As labile biologics, however, LVs pose critical challenges to industrial biomanufacturing. In particular, LV purification-currently reliant on filtration and anion-exchange or size-exclusion chromatography-suffers from long process times and low yield of transducing particles, which translate into high waiting time and cost to patients. Seeking to improve LV downstream processing, this study introduces peptides targeting the enveloped protein Vesicular stomatitis virus G (VSV-G) to serve as affinity ligands for the chromatographic purification of LV particles. An ensemble of candidate ligands was initially discovered by implementing a dual-fluorescence screening technology and a targeted in silico approach designed to identify sequences with high selectivity and tunable affinity. The selected peptides were conjugated on Poros resin and their LV binding-and-release performance was optimized by adjusting the flow rate, composition, and pH of the chromatographic buffers. Ligands GKEAAFAA and SRAFVGDADRD were selected for their high product yield (50%-60% of viral genomes; 40%-50% of HT1080 cell-transducing particles) upon elution in PIPES buffer with 0.65 M NaCl at pH 7.4. The peptide-based adsorbents also presented remarkable values of binding capacity (up to 3·109 TU per mL of resin, or 5·1011 vp per mL of resin, at the residence time of 1 min) and clearance of host cell proteins (up to a 220-fold reduction of HEK293 HCPs). Additionally, GKEAAFAA demonstrated high resistance to caustic cleaning-in-place (0.5 M NaOH, 30 min) with no observable loss in product yield and quality.

Exploring plant-derived small molecules as inhibitors of Marburg virus RNA binding protein activity

The search for antiviral medications is greatly influenced by the hunt for potent inhibitors of viral proteins. To find possible inhibitors of the RNA binding activity of the Marburg virus VP35 protein, we used a thorough in silico drug discovery approach in this investigation. A comprehensive virtual screening process, followed by a detailed MMGBSA analysis, led to the discovery of four potential inhibitory compounds viz. Kudzuisoflavone A, Miquelianin, Rutin, and Protopseudohypericin. They were identified from an extensive library of phytomolecules derived from three medicinal plants: Adiantum capillus-veneris, Hypericum perforatum, and Pueraria montana. In molecular dynamics (MD) simulations, all these compounds showed steady binding to the target protein and favourable interactions. Notably, the free binding energies of all the selected compounds were better than the myricetin, a well-known blocker of the VP35 protein of the Ebola virus. Overall, this investigation offers insightful information about the molecular interactions and binding dynamics of the identified inhibitors' binding to the VP35 protein of the Marburg virus. The findings highlight the potential of three particular medicinal plants as sources of key chemicals for the creation of brand-new Marburg virus antiviral drugs. More experimental validation and optimization of the identified inhibitors are necessary in order to transform these findings into effective medicines for treating Marburg virus infections.Communicated by Ramaswamy H. Sarma.

Mutation of two intronic nucleotides alters RNA structure and dynamics inhibiting MBNL1 and RBFOX1 regulated splicing of the Insulin Receptor

Alternative splicing (AS) of Exon 11 of the Insulin Receptor ( INSR ) is highly regulated and disrupted in several human disorders. To better understand INSR exon 11 AS regulation, splicing activity of an INSR exon 11 minigene reporter was measured across a gradient of the AS regulator muscleblind-like 1 protein (MBNL1). The RNA-binding protein Fox-1 (RBFOX1) was added to determine its impact on MBNL1-regulated splicing. The role of the RBFOX1 UGCAUG binding site within intron 11 was assessed across the MBNL1 gradient. Mutating the UGCAUG motif inhibited RBFOX1 regulation of exon 11 and had the unexpected effect of reducing MBNL1 regulation of this exon. Molecular dynamics simulations showed that exon 11 and the adjacent RNA adopts a dynamically stable conformation. Mutation of the RBFOX1 binding site altered RNA structure and dynamics, while a mutation that created an optimal MBNL1 binding site at the RBFOX1 site shifted the RNA back to wild type. An antisense oligonucleotide (ASO) was used to confirm the structure in this region of the pre-mRNA. This example of intronic mutations shifting pre-mRNA structure and dynamics to modulate splicing suggests RNA structure and dynamics should be taken into consideration for AS regulation and therapeutic interventions targeting pre-mRNA.

Structural and Dynamical Basis of VP35-RBD Inhibition by Marine Fungi Compounds to Combat Marburg Virus Infection

The Marburg virus (MBV), a deadly pathogen, poses a serious threat to world health due to the lack of effective treatments, calling for an immediate search for targeted and efficient treatments. In this study, we focused on compounds originating from marine fungi in order to identify possible inhibitory compounds against the Marburg virus (MBV) VP35-RNA binding domain (VP35-RBD) using a computational approach. We started with a virtual screening procedure using the Lipinski filter as a guide. Based on their docking scores, 42 potential candidates were found. Four of these compounds-CMNPD17596, CMNPD22144, CMNPD25994, and CMNPD17598-as well as myricetin, the control compound, were chosen for re-docking analysis. Re-docking revealed that these particular compounds had a higher affinity for MBV VP35-RBD in comparison to the control. Analyzing the chemical interactions revealed unique binding properties for every compound, identified by a range of Pi-cation interactions and hydrogen bond types. We were able to learn more about the dynamic behaviors and stability of the protein-ligand complexes through a 200-nanosecond molecular dynamics simulation, as demonstrated by the compounds' consistent RMSD and RMSF values. The multidimensional nature of the data was clarified by the application of principal component analysis, which suggested stable conformations in the complexes with little modification. Further insight into the energy profiles and stability states of these complexes was also obtained by an examination of the free energy landscape. Our findings underscore the effectiveness of computational strategies in identifying and analyzing potential inhibitors for MBV VP35-RBD, offering promising paths for further experimental investigations and possible therapeutic development against the MBV.

Rational design and experimental evaluation of peptide ligands for the purification of adeno-associated viruses via affinity chromatography

Adeno-associated viruses (AAVs) have acquired a central role in modern medicine as delivery agents for gene therapies targeting rare diseases. While new AAVs with improved tissue targeting, potency, and safety are being introduced, their biomanufacturing technology is lagging. In particular, the AAV purification pipeline hinges on protein ligands for the affinity-based capture step. While featuring excellent AAV binding capacity and selectivity, these ligands require strong acid (pH <3) elution conditions, which can compromise the product's activity and stability. Additionally, their high cost and limited lifetime has a significant impact on the price tag of AAV-based therapies. Seeking to introduce a more robust and affordable affinity technology, this study introduces a cohort of peptide ligands that (i) mimic the biorecognition activity of the AAV receptor (AAVR) and anti-AAV antibody A20, (ii) enable product elution under near-physiological conditions (pH 6.0), and (iii) grant extended reusability by withstanding multiple regenerations. A20-mimetic CYIHFSGYTNYNPSLKSC and AAVR-mimetic CVIDGSQSTDDDKIC demonstrated excellent capture of serotypes belonging to distinct clones/clades - namely, AAV1, AAV2, AAV5, AAV6, AAV8, and AAV9. This corroborates the in silico models documenting their ability to target regions of the viral capsid that are conserved across all serotypes. CVIDGSQSTDDDKIC-Toyopearl resin features binding capacity (≈1014 vp mL-1 ) and product yields (≈60%-80%) on par with commercial adsorbents, and purifies AAV2 from HEK293 and Sf9 cell lysates with high recovery (up to 78%), reduction of host cell proteins (up to 700-fold), and high transduction activity (up to 65%).

Estimation of the ice melting point in molecular dynamics simulations based on the finite-size effects

Predicting the ice melting point using molecular dynamics (MD) simulations is nontrivial due to uncertainty associated with the stochastic nature of the simulation and effect of finite domain sizes on the simulated ice-water phase transition. We developed a method based on the percolation theory to make use of the finite size effects to allow determination of a unique critical phase transition temperature as the melting point. The method involves construction of melting/freezing probability curves from multiple simulations with varying temperatures for different domain sizes. While the domain sizes affect the apparent melting/freezing probability and hence generate different curves with a wider probability distribution for a smaller size, the intersection of these curves is unique and locates the melting point. Based on MD simulations using the Tip4p/Ice water model, we tested and demonstrated the effectiveness of this method in locating the critical ice-water phase transition at a melting temperature of 268.78 K. Our analysis also showed that the apparent melting probability at this critical point is ∼0.69, not 0.5 assumed in the ad hoc method used previously. Our method, making no assumption about the system size, may provide a generic framework for analyzing phase transitions influenced by the finite size effects in MD simulations.

Virtual screening and molecular dynamics simulation approach for the identification of potential multi-target directed ligands for the treatment of Alzheimer's disease

Alzheimer's disease (AD) is a multifactorial neurological disorder characterized by memory loss and cognitive impairment. The currently available single-targeting drugs have miserably failed in the treatment of AD, and multi-target directed ligands (MTDLs) are being explored as an alternative treatment strategy. Cholinesterase and monoamine oxidase enzymes are reported to play a crucial role in the pathology of AD, and multipotent ligands targeting these two enzymes simultaneously are under various phases of design and development. Recent studies have revealed that computational approaches are robust and trusted tools for identifying novel therapeutics. The current research work is focused on the development of potential multi-target directed ligands that simultaneously inhibit acetylcholinesterase (AChE) and monoamine oxidase B (MAO-B) enzymes employing a structure-based virtual screening (SBVS) approach. The ASINEX database was screened after applying pan assay interference and drug-likeness filter to identify novel molecules using three docking precision criteria; High Throughput Virtual Screening (HTVS), Standard Precision (SP), and Extra Precision (XP). Additionally, binding free energy calculations, ADME, and molecular dynamic simulations were employed to get structural insights into the mechanism of protein-ligand binding and pharmacokinetic properties. Three lead molecules viz. AOP19078710, BAS00314308 and BDD26909696 were successfully identified with binding scores of -10.565, -10.543 & -8.066 kcal/mol against AChE and -11.019, -12.357 & -10.068 kcal/mol against MAO-B, better score as compared to the standard inhibitors. In the near future, these molecules will be synthesized and evaluated through in vitro and in vivo assays for their inhibition potential against AChE and MAO-B enzymes.

Exploring the role of microbial proteins in controlling environmental pollutants based on molecular simulation

Molecular simulation has been widely used to study microbial proteins' structural composition and dynamic properties, such as volatility, flexibility, and stability at the microscopic scale. Herein, this review describes the key elements of molecular docking and molecular dynamics (MD) simulations in molecular simulation; reviews the techniques combined with molecular simulation, such as crystallography, spectroscopy, molecular biology, and machine learning, to validate simulation results and bridge information gaps in the structure, microenvironmental changes, expression mechanisms, and intensity quantification; illustrates the application of molecular simulation, in characterizing the molecular mechanisms of interaction of microbial proteins with four different types of contaminants, namely heavy metals (HMs), pesticides, dyes and emerging contaminants (ECs). Finally, the review outlines the important role of molecular simulations in the study of microbial proteins for controlling environmental contamination and provides ideas for the application of molecular simulation in screening microbial proteins and incorporating targeted mutagenesis to obtain more effective contaminant control proteins.

Crystal structure determination, molecular docking, and molecular dynamics of arylal dimedones as potential inhibitors for castrate-resistant prostate cancer

Increased androgen receptor (AR) signaling brought on by higher intratumoral androgen production and AR amplification is associated with castrate-resistant prostate cancer (CRPC). Cell proliferation in this case continues even during low expression of testosterone in the body. Aldo-keto reductase family 1 member C3 (AKR1C3) is one of the most elevated genes in CRPC and catalyzes the formation of powerful AR ligands from inactive forms. The current work aimed to use the x-ray method to investigate the ligand's crystal structure while also conducting molecular docking and molecular dynamics tests on the synthesized molecules against AKR1C3. As per the results obtained, the MM-PBSA binding energies of inhibitors 2,2'-((4-methoxyphenyl)methylene)bis(3,4-hydroxy-5,5-dimethylcyclohex-2-en-1-one is -132.456 kJ mol-1 and 2,2'-(phenylmethylene)bis(3-hydroxy-5,5-dimethylcyclohex-2-en-1-one is -81.017 kJ mol-1 . These results create a promising approach to drug design based on its fit to the structures of the receptor site rather than basing it on analogies to other active structures.

Hop, Skip, and Jump: Hydrogen Molecular Transport through Amorphous Polyethylene Matrices Studied via Molecular Dynamics Simulations

In the pursuit of advancing and diversifying energy technologies for a more sustainable future, the possibilities of hydrogen (H2) usage will broaden, as will our understanding of its containment materials. Polyethylene (PE) has a vast assortment of uses and applications, which are growing with demands for alternative energy possibilities. One use of PE liner is as a prime candidate for nonmetallic piping and pressurized type IV storage devices. Such applications require PE to effectively prevent H2 transport through containment systems. To study the molecular transport mechanism of hydrogen through polymeric barriers, a system containing hydrogen molecules absorbed within amorphous PE is modeled here using molecular dynamics simulations. The simulations are conducted within a range of temperatures that span the glass transition temperature of amorphous PE. The simulated PE displays bulk density, radius of gyration, and self-diffusion coefficient that are consistent with experimental data. The simulated trajectories are interrogated to study the movement of the guest gas molecules. The results show that the diffusion coefficients increase with temperature, as expected. However, the mobility of the PE chains is found to affect the mobility of absorbed H2 molecules to a much lower extent than it affects that of CH4 molecules because of the much smaller size of the former than of the latter guest. From a molecular perspective, a "hopping" mechanism is observed, according to which H2 molecules hop between one vacant free volume space to another within the polymer matrix, in combination with longer, straight, undisturbed "jumps" or "skips" along directions aligned with regions of ordered PE chains. This suggests that the orientation of the crystallites within the semicrystalline PE matrix affects the H2 containment. Implications of these findings toward PE usage as containment material are discussed.

A high-throughput structural dynamics approach for identification of potential agonists of FFAR4 for type 2 diabetes mellitus therapy

Diabetes mellitus is a metabolic disorder that persists as a global threat to the world. A G-protein coupled receptor (GPCR), free fatty acid receptor 4 (FFAR4), has emerged as a potential target for type 2 diabetes mellitus (T2DM) and obesity-related disorders. The current study has investigated the FFAR4, deploying 3-dimensional structure modeling, molecular docking, machine learning, and high-throughput virtual screening methods to unravel the receptor's crucial and non-crucial binding site residues. We screened four lakh compounds and shortlisted them based on binding energy, stereochemical considerations, non-bonded interactions, and pharmacokinetic profiling. Out of the screened compounds, four compounds were selected for ligand-bound simulations. The molecular dynamic simulations were carried out for 1µs for native FFAR4 and 500 ns each for complexes of FFAR4 with compound 1, compound 2, compound 3, and compound 4. Our findings showed that in addition to reported binding site residues ARG99, ARG183, and VAL98 in known agonists like TUG-891, the amino acids ARG22, ARG24, THR23, TRP305, and GLU43 were also critical binding site residues. These amino acids impart stability to the FFAR4 complexes and contribute to the stronger binding affinity of the compounds. The study also indicated that aromatic residues like PHE211 are crucial for recognizing the active site's pi-pi and C-C double bonds. Since FFAR4 is a membrane protein, the simulation studies give an insight into the mechanisms of the crucial protein-lipid and lipid-water interactions. The analysis of the molecular dynamics trajectories showed all four compounds as potential hit molecules that can be developed further into potential agonists for T2DM therapy. Amongst the four compounds, compound 4 showed relatively better binding affinity, stronger non-bonded interactions, and a stable complex.Communicated by Ramaswamy H. Sarma.

A novel synthetic peptide analog enhanced antibacterial activity of the frog-derived skin peptide wuchuanin-A1

In recent years, there has been a growing focus on the development of novel antibacterial compounds for clinical applications, such as antimicrobial peptide (AMP). Among the developed AMP, wuchuanin-A1, a coil-shaped bioactive peptide derived from Odorrana wuchuanensis frog skin, has been reported to exhibit antibacterial, antifungal, and antioxidant activity, but there are limited studies on its potential as an antibacterial agent. Therefore, this study aims to molecularly modify the sequence of wuchuanin-A1 to enhance its antibacterial properties. The interaction of both the native and analog peptide with bacterial inner membranes was initially assessed using computational methods. Specific amino acid substitutions were then used to enhance the modified peptide's antibacterial efficacy, followed by several preliminary tests to evaluate its activity. This study bridges the gap in exploring the potential of wuchuanin-A1 for antibacterial purposes, providing insights into the design of effective antimicrobial agents.Communicated by Ramaswamy H. Sarma.

Molecular scale behavior of xylan during solvent-controlled extraction and precipitation

Solvent-controlled extraction and precipitation are the most fundamental methods for obtaining hemicellulose from lignocellulosic biomass and purification processes. However, the dissolution and precipitation mechanisms involved have scarcely been mentioned. In this study, the molecular scale behavior of xylan-type hemicellulose during solvent-controlled extraction and precipitation is investigated using molecular dynamics (MD) simulations and density functional theory (DFT) calculations. To bring the model closer to the real extracted xylan, a high degree of polymerization (DP100) of xylan is established, and hemicelluloses with low DP (DP15 and DP50) are also investigated. Four phenomena are explained at the molecular level, including the influence of the polymerization degree and side chain on the solubility of xylan in water, the improvement of the xylan's solubility in NaOH, the precipitation of xylan in ethanol, and the acetyl group preservation of xylan in DMSO. This study contributes to an increased understanding of the dissolution and precipitation mechanisms of hemicellulose and provides a resource for the simulation of high DP hemicellulose, which gives a theoretical basis for the efficient extraction of high-purity hemicellulose as well as economic biorefining.

In silico computational drug discovery: a Monte Carlo approach for developing a novel JAK3 inhibitors

Inhibition of Janus kinase 3 (JAK3), a member of the JAK family of tyrosine kinases, remains an essential area of research for developing treatments for autoimmune diseases, particularly cancer and rheumatoid arthritis. The recent discovery of a new JAK3 protein, PDB ID: 4Z16, offers exciting possibilities for developing inhibitors capable of forming a covalent bond with the Cys909 residue, thereby contributing to JAK3 inhibition. A powerful prediction model was constructed and validated using Monte Carlo methods, employing various internal and external techniques. This approach resulted in the prediction of eleven new molecules, which were subsequently filtered to identify six compounds exhibiting potent pIC50 values. These candidates were then subjected to ADMET analysis, molecular docking (including reversible-reversible docking with tofacitinib, an FDA-approved drug, and reversible-irreversible docking for the newly designed compounds), molecular dynamics (MD) analysis for 300 ns, and calculation of free binding energy. The results suggested that these compounds hold promise as JAK3 inhibitors. In summary, the new compounds have exhibited favorable outcomes compared to other compounds across various modeling approaches. The collective findings from these investigations provide valuable insights into the potential therapeutic applications of covalent JAK3 inhibitors, offering a promising direction for the development of novel treatments for autoimmune disorders.Communicated by Ramaswamy H. Sarma.

Comparative Analysis of Conformational Dynamics and Systematic Characterization of Cryptic Pockets in the SARS-CoV-2 Omicron BA.2, BA.2.75 and XBB.1 Spike Complexes with the ACE2 Host Receptor: Confluence of Binding and Structural Plasticity in Mediating Networks of Conserved Allosteric Sites

In the current study, we explore coarse-grained simulations and atomistic molecular dynamics together with binding energetics scanning and cryptic pocket detection in a comparative examination of conformational landscapes and systematic characterization of allosteric binding sites in the SARS-CoV-2 Omicron BA.2, BA.2.75 and XBB.1 spike full-length trimer complexes with the host receptor ACE2. Microsecond simulations, Markov state models and mutational scanning of binding energies of the SARS-CoV-2 BA.2 and BA.2.75 receptor binding domain complexes revealed the increased thermodynamic stabilization of the BA.2.75 variant and significant dynamic differences between these Omicron variants. Molecular simulations of the SARS-CoV-2 Omicron spike full-length trimer complexes with the ACE2 receptor complemented atomistic studies and enabled an in-depth analysis of mutational and binding effects on conformational dynamic and functional adaptability of the Omicron variants. Despite considerable structural similarities, Omicron variants BA.2, BA.2.75 and XBB.1 can induce unique conformational dynamic signatures and specific distributions of the conformational states. Using conformational ensembles of the SARS-CoV-2 Omicron spike trimer complexes with ACE2, we conducted a comprehensive cryptic pocket screening to examine the role of Omicron mutations and ACE2 binding on the distribution and functional mechanisms of the emerging allosteric binding sites. This analysis captured all experimentally known allosteric sites and discovered networks of inter-connected and functionally relevant allosteric sites that are governed by variant-sensitive conformational adaptability of the SARS-CoV-2 spike structures. The results detailed how ACE2 binding and Omicron mutations in the BA.2, BA.2.75 and XBB.1 spike complexes modulate the distribution of conserved and druggable allosteric pockets harboring functionally important regions. The results are significant for understanding the functional roles of druggable cryptic pockets that can be used for allostery-mediated therapeutic intervention targeting conformational states of the Omicron variants.

De novo design of anti-variant COVID-19 vaccine

Recent studies highlight the effectiveness of hybrid Severe Acute Respiratory Syndrome-Coronavirus-2 (SARS-CoV-2) vaccines combining wild-type nucleocapsid and Spike proteins. We have further enhanced this strategy by incorporating delta and omicron variants' spike protein mutations. Both delta and omicron mark the shifts in viral transmissibility and severity in unvaccinated and vaccinated patients. So their mutations are highly crucial for future viral variants also. Omicron is particularly adept at immune evasion by mutating spike epitopes. The rapid adaptations of Omicron and sub-variants to spike-based vaccines and simultaneous transmissibility underline the urgency for new vaccines in the continuous battle against SARS-CoV-2. Therefore, we have added three persistent T-cell-stimulating nucleocapsid peptides similar to homologous sequences from seasonal Human Coronaviruses (HuCoV) and an envelope peptide that elicits a strong T-cell immune response. These peptides are clustered in the hybrid spike's cytoplasmic region with non-immunogenic linkers, enabling systematic arrangement. AlphaFold (Artificial intelligence-based model building) analysis suggests omitting the transmembrane domain enhances these cytoplasmic epitopes' folding efficiency which can ensure persistent immunity for CD4+ structural epitopes. Further molecular dynamics simulations validate the compact conformation of the modeled structures and a flexible C-terminus region. Overall, the structures show stability and less conformational fluctuation throughout the simulation. Also, the AlphaFold predicted structural epitopes maintained their folds during simulation to ensure the specificity of CD4+ T-cell response after vaccination. Our proposed approach may provide options for incorporating diverse anti-viral T-cell peptides, similar to HuCoV, into linker regions. This versatility can be promising to address outbreaks and challenges posed by various viruses for effective management in this era of innovative vaccines.

Bioaccessibility of polypropylene microfiber-associated tetracycline and ciprofloxacin in simulated human gastrointestinal fluids

Microplastics residues in natural waters can adsorb organic contaminants owing to their rough surface morphology and high specific surface area, potentially harming human health when ingested. Although humans inevitably ingest microplastics, the bioaccessibility of microplastic-associated chemicals in the human gastric and intestinal fluids remains unresolved. This study investigated the mechanism and primary factor controlling the bioaccessibility of polypropylene (PP) microplastic fiber-associated tetracycline (TC) and ciprofloxacin (CIP) in simulated human gastrointestinal fluids. After mixing 0.1 g of PP microfiber with 10 mg/L of TC (or CIP) for 96 h and exposure to simulated human gastrointestinal fluids, the TC concentrations were 0.440, 0.678, and 1.840 mg/L and the CIP concentrations were 0.700, 1.367, and 3.281 mg/L CIP in the simulated human saliva, gastric, and intestinal fluids after incubation for 60 s, 4 h, and 8 h, respectively. This indicated that the antibiotics TC and CIP adsorbed onto microfiber surface are readily released into human gastrointestinal fluids upon ingestion. Gastric and intestinal fluids showed enhanced bioaccessibility to TC/CIP adhered to PP microfiber. The primary factors affecting the bioaccessibility to TC/CIP adhered to PP microfiber surfaces were found to be pepsin in human gastric fluid and trypsin in human intestinal fluid. Molecular docking and simulated molecular dynamic analyses results showed that pepsin and trypsin stablish connections with TC via hydrogen bonds (reaction sites: pepsin TC: T139, T136, S97, D94, D277 and Y251; trypsin TC: S257, H120, K235, G274, and G276) and CIP via hydrophobic interactions (reaction sites: pepsin CIP: Y137, T136, T139, F173, I362, V353, and I275; trypsin CIP: W273, I161, C253, and C277). Our findings highlight that microplastic ingestion increases the risk of microplastics and the co-contaminants adsorbed to human health; thus, these findings are helpful to assess the risk of microplastics and co-contaminants to human health.

In-silico modeling of the interplay between APOE4, NLRP3, and ACE2-SPIKE complex in neurodegeneration between Alzheimer and SARS-CoV: implications for understanding pathogenesis and developing therapeutic strategies

The multifaceted interplay between neurodegenerative pathologies, including Alzheimer's disease (AD), and the highly virulent severe acute respiratory syndrome coronavirus (SARS-CoV), is implicated in various conditions. AD and SARS-CoV pathogenesis involve the APOE4 allele, NLRP3 inflammasome, and ACE2-SPIKE complex. APOE4, a genetic polymorphism of the APOE gene, is associated with an increased susceptibility to AD. NLRP3, an inflammatory protein of the innate immune system, plays a pivotal role in immune response cascades. In SARS-CoV, the ACE2 receptor serves as the principal portal for cellular entry, while APOE4 intricately interacts with the ACE2-spike protein complex, enhancing viral internalization process. The interaction of NLRP3 with the ACE2-spike protein complex leads to increased inflammatory signaling. The convergence of APOE4/NLRP3 and ACE2-spike protein complex interactions suggests a possible link between SARS and AD. Therefore, the current research centralizes the association between by utilizing SARS-CoV datasets to explore possible mechanisms that account for the pathogenesis of SARS-CoV and AD. The work is further extended to unveil the molecular interactions of APOE4 and NLRP3 with the ACE2-Spike protein complex at the molecular level by employing molecular dynamics simulation techniques. The therapeutic efficacy of Chyawanprash nutraceuticals is evaluated as their inhibitory potential towards APOE4-ACE2-Spike protein and NLRP3-ACE2-Spike protein complexes. Notably, our simulations unequivocally demonstrate the robust and enduring binding capability of the compound Phyllantidine with the target complexes throughout the simulation period. The findings of the studies further corroborate the primary hypothesis of APOE4 and NLRP3 as driver factors in the pathogenesis of both SARS-CoV and AD. Therefore, this research establishes a paradigm for comprehending the complex interaction between AD and SARS-CoV and lays the groundwork for further study in this domain.Communicated by Ramaswamy H. Sarma.

Mercapto-pyrimidines are reversible covalent inhibitors of the papain-like protease (PLpro) and inhibit SARS-CoV-2 (SCoV-2) replication

The papain-like protease (PLpro) plays a critical role in SARS-CoV-2 (SCoV-2) pathogenesis and is essential for viral replication and for allowing the virus to evade the host immune response. Inhibitors of PLpro have great therapeutic potential, however, developing them has been challenging due to PLpro's restricted substrate binding pocket. In this report, we screened a 115 000-compound library for PLpro inhibitors and identified a new pharmacophore, based on a mercapto-pyrimidine fragment that is a reversible covalent inhibitor (RCI) of PLpro and inhibits viral replication in cells. Compound 5 had an IC50 of 5.1 μM for PLpro inhibition and hit optimization yielded a derivative with increased potency (IC50 0.85 μM, 6-fold higher). Activity based profiling of compound 5 demonstrated that it reacts with PLpro cysteines. We show here that compound 5 represents a new class of RCIs, which undergo an addition elimination reaction with cysteines in their target proteins. We further show that their reversibility is catalyzed by exogenous thiols and is dependent on the size of the incoming thiol. In contrast, traditional RCIs are all based upon the Michael addition reaction mechanism and their reversibility is base-catalyzed. We identify a new class of RCIs that introduces a more reactive warhead with a pronounced selectivity profile based on thiol ligand size. This could allow the expansion of RCI modality use towards a larger group of proteins important for human disease.

Parsing structural fragments of thiazolidin-4-one based α-amylase inhibitors: A combined approach employing in vitro colorimetric screening and GA-MLR based QSAR modelling supported by molecular docking, molecular dynamics simulation and ADMET studies

α-Amylase (EC.3.2.1.1) is a ubiquitous digestive endoamylase. The abrupt rise in blood glucose levels due to the hydrolysis of carbohydrates by α-amylase at a faster rate is one of the main reasons for type 2 diabetes. The inhibitors prevent the action of digestive enzymes, slowing the digestion of carbs and eventually assisting in the management of postprandial hyperglycemia. In the course of developing α-amylase inhibitors, we have screened 2-aryliminothiazolidin-4-one based analogs for their in vitro α-amylase inhibitory potential and employed various in silico approaches for the detailed exploration of the bioactivity. The DNSA bioassay revealed that compounds 5c, 5e, 5h, 5j, 5m, 5o and 5t were more potent than the reference drug (IC₆₀ value = 22.94 ± 0.24 μg mL^-1). The derivative 5o with -NO₂ group at both the rings was the most potent analog with an IC₆₀ value of 19.67 ± 0.20 μg mL^-1 whereas derivative 5a with unsubstituted aromatic rings showed poor inhibitory potential with an IC₆₀ value of 33.40 ± 0.15 μg mL^-1. The reliable QSAR models were developed using the QSARINS software. The high value of R²_ext = 0.9632 for model IM-9 showed that the built model can be applied to predict the α-amylase inhibitory activity of the untested molecules. A consensus modelling approach was also employed to test the reliability and robustness of the developed QSAR models. Molecular docking and molecular dynamics were employed to validate the bioassay results by studying the conformational changes and interaction mechanisms. A step further, these compounds also exhibited good ADMET characteristics and bioavailability when tested for in silico pharmacokinetics prediction parameters.

Temperature dependence of DNA elasticity: An all-atom molecular dynamics simulation study

We used all-atom molecular dynamics simulation to investigate the elastic properties of double-stranded DNA (dsDNA). We focused on the influences of temperature on the stretch, bend, and twist elasticities, as well as the twist-stretch coupling, of the dsDNA over a wide range of temperature. The results showed that the bending and twist persistence lengths, together with the stretch and twist moduli, decrease linearly with temperature. However, the twist-stretch coupling behaves in a positive correction and enhances as the temperature increases. The potential mechanisms of how temperature affects dsDNA elasticity and coupling were investigated by using the trajectories from atomistic simulation, in which thermal fluctuations in structural parameters were analyzed in detail. We analyzed the simulation results by comparing them with previous simulation and experimental data, which are in good agreement. The prediction about the temperature dependence of dsDNA elastic properties provides a deeper understanding of DNA elasticities in biological environments and potentially helps in the further development of DNA nanotechnology.

The Relationship between Structure and Performance of Different Polyimides Based on Molecular Simulations

A polyimide (PI) molecular model was successfully constructed to compare the performance of PIs with different structures. In detail, the structure of the cross-linked PI resin, the prepolymer melt viscosity, and the glass-transition temperature (T_g) were investigated using molecular simulations. The results indicate that benzene ring and polyene-type cross-linked structures dominate the properties of the PIs. Moreover, the prepolymer melt viscosity simulations show that the 6FDA-APB and the ODPA-APB systems have a low viscosity. The results for the T_g and the distribution dihedral angle reveal that the key factor affecting bond flexibility may be the formation of a new dihedral angle after cross-linking, which affects the T_g. The above results provide an important reference for the design of PIs and have important value from the perspective of improving the efficiency of new product development.

How do salt and lipids affect conformational dynamics of Aβ42 monomers in water?

It is well established that amyloid β-protein (Aβ) self-assembly is involved in triggering of Alzheimer's disease. On the other hand, evidence of physiological function of Aβ interacting with lipids has only begun to emerge. Details of Aβ-lipid interactions, which may underlie physiological and pathological activities of Aβ, are not well understood. Here, the effects of salt and 1,2-dimyristoyl-sn-glycero-3-phosphocholine (DMPC) lipids on conformational dynamics of Aβ42 monomer in water are examined by all-atom molecular dynamics (MD). We acquired six sets of 250 ns long MD trajectories for each of the three lipid concentrations (0, 27, and 109 mM) in the absence and presence of 150 mM salt. Ten replica trajectories per set are used to enhance sampling of Aβ42 conformational space. We show that salt facilitates long-range tertiary contacts in Aβ42, resulting in more compact Aβ42 conformations. By contrast, addition of lipids results in lipid-concentration dependent Aβ42 unfolding concomitant with enhanced stability of the turn in the A21-A30 region. At the high lipid concentration, salt enables the N-terminal region of Aβ42 to form long-range tertiary contacts and interact with lipids, which results in formation of a parallel β-strand. Aβ42 forms stable lipid-protein complexes whereby the protein is adhered to the lipid cluster rather than embedded into it. We propose that the inability of Aβ42 monomer to get embedded into the lipid cluster may be important for facilitating repair of leaks in the blood-brain barrier without penetrating and damaging cellular membranes.

Fully Atomistic Molecular Dynamics Simulation of a TIPS-Pentacene:Polystyrene Mixed Film Obtained via the Solution Process

Organic thin-film transistors using small-molecule semiconductor materials such as 6,13-bis(triisopropylsilylethynyl)pentacene (TIPS-P) have been recently studied for the production of flexible and printed electronic devices. Blending a semiconductor with an insulating polymer, such as polystyrene, is known to improve the device performance; however, its molecular-level structure remains unknown. In this study, we performed molecular dynamics (MD) simulations on a mixed system of TIPS-P and atactic polystyrene (aPS) with fully atomistic models to understand the structure of the mixed thin film at the molecular level and the influence on the device properties. To reproduce the deposition from the solution, we gradually reduced the number of toluene molecules in the simulation. The dynamic characteristics of the system, mean squared displacement, diffusion coefficient, density profile, and P₂ order parameter were analyzed. Some of the simulated systems reached the equilibrium state. In these systems, the simulated structures suggested the presence of more TIPS-P molecules on the surface than inside the bulk, even at the low molecular weight of aPS, where phase separation was not observed experimentally. The results of the fully atomistic MD simulations are also a basis for the coarse-grained model to increase the speed of the MD simulation.

Computational Design of Phosphatidylinositol 3-Kinase Inhibitors

One of the most sought-after therapeutic targets for treating human cancers is the phosphoinositide 3-kinase; PI3k is an integral part of the PI3K/protein kinase B signaling arcade. This pathway is frequently activated in malignancies. Drug resistance and dose-limiting adverse effects are currently associated challenges with the existing anticancer chemotherapy. Therefore, in this research, a series of pyrimidine derivatives were designed and evaluated against human PI3K by using molecular docking analysis. The docking results were further verified by molecular dynamic simulation, which analyzed the strength of the macromolecular complex with respect to time. Compounds IV and XIV were found to be the most potent inhibitors of the human PI3K receptor with a high degree of stability within the active site of the target receptor for a timeframe of 50 ns. Thus, both of these compounds could be important drug candidates for the development of PI3K inhibitors as a prospective anticancer agent.