The double cubic lattice method: Efficient approaches to numerical integration of surface area and volume and to dot surface contouring of molecular assemblies

Inhibitory Potential of the Truncated Isoforms on Glutamate Transporter Oligomerization Identified by Computational Analysis of Gene-Centric Isoform Maps

OBJECTIVE

Glutamate transporters play a key role in central nervous system physiology by maintaining excitatory neurotransmitter homeostasis. Biological assemblies of the transporters, consisting of cyclic homotrimers, emerge as a crucial aspect of glutamate transporter modulation. Hence targeting heteromerization promises an effective approach for modulator design. On the other hand, the dynamic nature of transcription allows for the generation of transporter isoforms in structurally distinct manners.

METHODS

The potential isoforms were identified through the analysis of computationally generated gene-centric isoform maps. The conserved features of isoform sequences were revealed by computational chemistry methods and subsequent structural analysis of AlphaFold2 predictions. Truncated isoforms were further subjected to a wide range of docking analyses, 50ns molecular dynamics simulations, and evolutionary coupling analyses.

RESULTS

Energetic landscapes of isoform-canonical transporter complexes suggested an inhibitory potential of truncated isoforms on glutamate transporter bio-assembly. Moreover, isoforms that mimic the trimerization domain (in particular, TM2 helices) exhibited stronger interactions with canonical transporters, underscoring the role of transmembrane helices in isoform interactions. Additionally, self-assembly dynamics observed in truncated isoforms mimicking canonical TM5 helices indicate a potential protective role against unwanted interactions with canonical transporters.

CONCLUSION

Our computational studies on glutamate transporters offer insights into the roles of alternative splicing on protein interactions and identifies potential drug targets for physiological or pathological processes.

Acetylation-Dependent Compaction of the Histone H4 Tail Ensemble

Acetylation of the histone H4 tail (H4Kac) has been established as a significant regulator of chromatin architecture and accessibility; however, the molecular mechanisms that underlie these observations remain elusive. Here, we characterize the ensemble features of the histone H4 tail and determine how they change following acetylation on specific sets of lysine residues. Our comprehensive account is enabled by a robust combination of experimental and computational biophysical methods that converge on molecular details including conformer size, intramolecular contacts, and secondary structure propensity. We find that acetylation significantly alters the chemical environment of basic patch residues (16-20) and leads to tail compaction that is partially mediated by transient intramolecular contacts established between the basic patch and N-terminal amino acids. Beyond acetylation, we identify that the protonation state of H18, which is affected by the acetylation state, is a critical regulator of ensemble characteristics, highlighting the potential for interplay between the sequence context and post-translational modifications to define the ensemble features of intrinsically disordered regions. This study elucidates molecular details that could link H4Kac with the regulation of chromatin architecture, illuminating a small piece of the complex network of molecular mechanisms underlying the histone code hypothesis.

Cm-p5, a molluscan-derived antifungal peptide exerts its activity by a membrane surface covering in a non-penetrating mode

Amidst the health crisis caused by the rise of multi-resistant pathogenic microorganisms, Antimicrobial Peptides (AMPs) have emerged as a potential alternative to traditional antibiotics. In this sense, Cm-p5 is an AMP with fungistatic activity against the yeast Candida albicans. Its antimicrobial activity and selectivity have been well characterized; however, the mechanism of action is still unknown. This study used biophysical approaches to gain insight into how this peptide exerts its activity. Stability and fluidity of lipid membrane were explored by liposome leakage and Laurdan generalized polarization (GP) respectively, suggesting that Cm-p5 does not perturb lipid membranes even at very high concentrations (≥100µm.L-1). Likewise, no depolarizing action was observed using 3,3'-propil-2,2'-thyodicarbocianine, a potential membrane fluorescent reporter, with C. albicans cells or the corresponding liposome models. Changes in liposome size were analyzed by Dynamic Light Scattering (DLS) data, indicating that Cm-p5 covers the vesicular surface slightly increasing liposome hydrodynamic size, without liposome rupture. These results were further corroborated with Langmuir monolayer isotherms, where no significant changes in lateral pressure or area per lipid were detected, indicating little or no insertion. Finally, data obtained from molecular dynamics simulations aligned with in vitro observations, whereby Cm-p5 slightly interacted with the fungal membrane model surface without causing significant perturbation. These results suggest Cm-p5 is not a pore-forming anti-fungal peptide and that other mechanisms of action on the membrane as some limitation of fungal nutrition or receptor-dependent transduction for depressing growth development should be explored.

Ionizable Cationic Lipids and Helper Lipids Synergistically Contribute to RNA Packing and Protection in Lipid-Based Nanomaterials

Lipid-based nanomaterials are used as a common delivery vehicle for RNA therapeutics. They typically include a formulation containing ionizable cationic lipids, cholesterol, phospholipids, and a small molar fraction of PEGylated lipids. The ionizable cationic lipids are considered a crucial element of the formulation for the way they mediate interactions with the anionic RNA as a function of pH. Here, we show, by means of molecular dynamics simulation of lipid formulations containing two different ionizable cationic lipids (DLinDMA and DLinDAP), that the direct interactions of those lipids with RNA, taken alone, may not be sufficient to determine the level of protection and packaging of mRNA. Our simulations help and highlight how the collective behavior of the lipids in the formulation, which determines the ability to envelop the RNA, and the level of hydration of the lipid-RNA interface may also play a significant role. This allows the drawing of a hypothesis about the experimentally observed differences in the transfection efficiency of the two ionizable cationic lipids.

Molecular Dynamics Reveal Key Steps in BAR-Related Membrane Remodeling

Endocytosis plays a complex role in pathogen-host interactions. It serves as a pathway for pathogens to enter the host cell and acts as a part of the immune defense mechanism. Endocytosis involves the formation of lipid membrane vesicles and the reshaping of the cell membrane, a task predominantly managed by proteins containing BAR (Bin1/Amphiphysin/yeast RVS167) domains. Insights into how BAR domains can remodel and reshape cell membranes provide crucial information on infections and can aid the development of treatment. Aiming at deciphering the roles of the BAR dimers in lipid membrane bending and remodeling, we conducted extensive all-atom molecular dynamics simulations and discovered that the presence of helix kinks divides the BAR monomer into two segments-the "arm segment" and the "core segment"-which exhibit distinct movement patterns. Contrary to the prior hypothesis of BAR domains working as a rigid scaffold, we found that it functions in an "Arms-Hands" mode. These findings enhance the understanding of endocytosis, potentially advancing research on pathogen-host interactions and aiding in the identification of new treatment strategies targeting BAR domains.

Structure and Dynamics of Water in Polysaccharide (Alginate) Solutions and Gels Explained by the Core-Shell Model

In both biological and engineered systems, polysaccharides offer a means of establishing structural stiffness without altering the availability of water. Notable examples include the extracellular matrix of prokaryotes and eukaryotes, artificial skin grafts, drug delivery materials, and gels for water harvesting. Proper design and modeling of these systems require detailed understanding of the behavior of water confined in pores narrower than about 1 nm. We use molecular dynamics simulations to investigate the properties of water in solutions and gels of the polysaccharide alginate as a function of the water content and polymer cross-linking. We find that a detailed understanding of the nanoscale dynamics of water in alginate solutions and gels requires consideration of the discrete nature of water. However, we also find that the trends in tortuosity, permeability, dielectric constant, and shear viscosity can be adequately represented using the "core-shell" conceptual model that considers the confined fluid as a continuum.

Computational assessment of lipid facilitated membrane permeation of vancomycin using force-probe molecular dynamic simulation

In this study the efficacy of different edible lipids for drug permeation enhancement of vancomycin through biological membrane was investigated using molecular dynamic simulation. In this regard, at first the ability of the lipids for complex formation with the drug was evaluated for number of most common edible lipids including tripalmitin (TPA), trimyristin (TMY), labrafil (LAB), glycerol monostearate (GMS), glycerol monooleate (GMO), Distearoylphosphorylethanolamine (DSPE), dipalmitoylphosphatidylethanolamine (DPPE), Dipalmitoylphosphatidylcholine (DPPC), cholesterol (CL), stearic acid (SA), palmitic acid (PA) and oleic acid (OA). Then the complexes were pulled thorough a bilayer membrane while the changes in force were probed. The results showed that besides the SA, PA and OA the other examined lipids were able to perform a perfect molecular complex with the drug. Also the results of pulling simulation revealed that the least of force was needed for drug transmittance through the membrane when it was covered by LAB, TMY and DSPE. These results indicated that these lipids can be the excellent materials of choice as permeation enhancer for preparing a proper oral formulation of vancomycin.Communicated by Ramaswamy H. Sarma.

Functionalized Amorphous Carbon Materials via Reactive Molecular Dynamics Simulations

We derive a database of atomistic structural models of amorphous carbon materials endowed with exohedral functional groups. We start from phases previously derived using the DynReaxMas method for reactive molecular dynamics simulations, which exhibit atomistic and medium-length-scale features in excellent agreement with available experimental data. Given a generic input structure/phase, we develop postprocessing simulation algorithms mimicking experimental preparation protocols aimed at: (1) "curing" the phase to decrease the defect concentration; (2) automatically selecting the most reactive carbon atoms via interaction with a probe molecular species, and (3) stabilizing the phase by saturating the valence of carbon atoms with single-bond functional groups. Although we focus on oxygen-bearing functionalities, they can be replaced with other monovalent groups, such as -H, -COOH, -CHO, so that the protocol is quite general. We finally classify reactive sites in terms of their location within the structural framework and coordination environment (edges, tunnels, rings, aromatic carbons becoming aliphatic) and try to single out descriptors that correlate with tendency to functionalization.

AbMelt: Learning antibody thermostability from molecular dynamics

Antibody thermostability is challenging to predict from sequence and/or structure. This difficulty is likely due to the absence of direct entropic information. Herein, we present AbMelt where we model the inherent flexibility of homologous antibody structures using molecular dynamics simulations at three temperatures and learn the relevant descriptors to predict the temperatures of aggregation (Tagg), melt onset (Tm,on), and melt (Tm). We observed that the radius of gyration deviation of the complementarity determining regions at 400 K is the highest Pearson correlated descriptor with aggregation temperature (rp = -0.68 ± 0.23) and the deviation of internal molecular contacts at 350 K is the highest correlated descriptor with both Tm,on (rp = -0.74 ± 0.04) as well as Tm (rp = -0.69 ± 0.03). Moreover, after descriptor selection and machine learning regression, we predict on a held-out test set containing both internal and public data and achieve robust performance for all endpoints compared with baseline models (Tagg R2 = 0.57 ± 0.11, Tm,on R2 = 0.56 ± 0.01, and Tm R2 = 0.60 ± 0.06). In addition, the robustness of the AbMelt molecular dynamics methodology is demonstrated by only training on <5% of the data and outperforming more traditional machine learning models trained on the entire data set of more than 500 internal antibodies. Users can predict thermostability measurements for antibody variable fragments by collecting descriptors and using AbMelt, which has been made available.

Templated Nucleation of Clotrimazole and Ketoprofen on Polymer Substrates

The use of different template surfaces in crystallization experiments can directly influence the nucleation kinetics, crystal growth, and morphology of active pharmaceutical ingredients (APIs). Consequently, templated nucleation is an attractive approach to enhance crystal nucleation kinetics and preferentially nucleate desired crystal polymorphs for solid-form drug molecules, particularly large and flexible molecules that are difficult to crystallize. Herein, we investigate the effect of polymer templates on the crystal nucleation of clotrimazole and ketoprofen with both experiments and computational methods. Crystallization was carried out in toluene solvent for both APIs with a template library consisting of 12 different polymers. In complement to the experimental studies, we developed a computational workflow based on molecular dynamics (MD) and derived descriptors from the simulations to score and rank API-polymer interactions. The descriptors were used to measure the energy of interaction (EOI), hydrogen bonding, and rugosity (surface roughness) similarity between the APIs and polymer templates. We used a variety of machine learning models (14 in total) along with these descriptors to predict the crystallization outcome of the polymer templates. We found that simply rank-ordering the polymers by their API-polymer interaction energy descriptors yielded 92% accuracy in predicting the experimental outcome for clotrimazole and ketoprofen. The most accurate machine learning model for both APIs was found to be a random forest model. Using these models, we were able to predict the crystallization outcomes for all polymers. Additionally, we have performed a feature importance analysis using the trained models and found that the most predictive features are the energy descriptors. These results demonstrate that API-polymer interaction energies are correlated with heterogeneous crystallization outcomes.

Structure and dynamics of cholesterol-mediated aquaporin-0 arrays and implications for lipid rafts

Aquaporin-0 (AQP0) tetramers form square arrays in lens membranes through a yet unknown mechanism, but lens membranes are enriched in sphingomyelin and cholesterol. Here, we determined electron crystallographic structures of AQP0 in sphingomyelin/cholesterol membranes and performed molecular dynamics (MD) simulations to establish that the observed cholesterol positions represent those seen around an isolated AQP0 tetramer and that the AQP0 tetramer largely defines the location and orientation of most of its associated cholesterol molecules. At a high concentration, cholesterol increases the hydrophobic thickness of the annular lipid shell around AQP0 tetramers, which may thus cluster to mitigate the resulting hydrophobic mismatch. Moreover, neighboring AQP0 tetramers sandwich a cholesterol deep in the center of the membrane. MD simulations show that the association of two AQP0 tetramers is necessary to maintain the deep cholesterol in its position and that the deep cholesterol increases the force required to laterally detach two AQP0 tetramers, not only due to protein-protein contacts but also due to increased lipid-protein complementarity. Since each tetramer interacts with four such 'glue' cholesterols, avidity effects may stabilize larger arrays. The principles proposed to drive AQP0 array formation could also underlie protein clustering in lipid rafts.

Effects of an external static EF on the conformational transition of 5-HT1A receptor: A molecular dynamics simulation study

The serotonin receptor subtype 1A (5-HT1AR), one of the G-protein-coupled receptor (GPCR) family, has been implicated in several neurological conditions. Understanding the activation and inactivation mechanism of 5-HT1AR at the molecular level is critical for discovering novel therapeutics in many diseases. Recently there has been a growing appreciation for the role of external electric fields (EFs) in influencing the structure and activity of biomolecules. In this study, we used molecular dynamics (MD) simulations to examine conformational features of active states of 5-HT1AR and investigate the effect of an external static EF with 0.02 V/nm applied on the active state of 5-HT1AR. Our results showed that the active state of 5-HT1AR maintained the native structure, while the EF led to structural modifications in 5-HT1AR, particularly inducing the inward movement of transmembrane helix 6 (TM6). Furthermore, it disturbed the conformational switches associated with activation in the CWxP, DRY, PIF, and NPxxY motifs, consequently predisposing an inclination towards the inactive-like conformation. We also found that the EF led to an overall increase in the dipole moment of 5-HT1AR, encompassing TM6 and pivotal amino acids. The analyses of conformational properties of TM6 showed that the changed secondary structure and decreased solvent exposure occurred upon the EF condition. The interaction of 5-HT1AR with the membrane lipid bilayer was also altered under the EF. Our findings reveal the molecular mechanism underlying the transition of 5-HT1AR conformation induced by external EFs, which offer potential novel insights into the prospect of employing structure-based EF applications for GPCRs.

Helicity-directed recognition of bacterial phospholipid via radially amphiphilic antimicrobial peptides

The fundamental differences in phospholipids between bacterial and mammalian cell membranes present remarkable opportunities for antimicrobial design. However, it is challenging to distinguish bacterial anionic phospholipid phosphatidylglycerol (PG) from mammalian anionic phosphatidylserine (PS) with the same net charge. Here, we report a class of radially amphiphilic α helix antimicrobial peptides (RAPs) that can selectively discriminate PG from PS, relying on the helix structure. The representative RAP, L10-MMBen, can direct the rearrangement of PG vesicles into a lamellar structure with its helix axis parallel to the PG membrane surface. The helical structure imparts both the thermodynamic and kinetic advantages of L10-MMBen/PG assembly, and the hiding of hydrophobic regions in RAPs is crucial for PG recognition. L10-MMBen exhibits high selectivity against bacteria depending on PG recognition, showing low in vivo toxicity and significant treatment efficacy in mice infection models. Our study introduces a helicity-direct bacterial phospholipid recognition paradigm for designing highly selective antimicrobial peptides.

Solvent quality and nonbiological oligomer folding: revisiting conventional paradigms

We report on extensive molecular dynamics atomistic simulations of a meta-substituted poly-phenylacetylene (pPA) foldamer dispersed in three solvents, water H2O, cyclohexane cC6H12, and n-hexane nC6H14, and for three oligomer lengths 12mer, 16mer and 20mer. At room temperature, we find a tendency of the pPA foldamer to collapse into a helical structure in all three solvents but with rather different stability character, stable in water, marginally stable in n-hexane, unstable in cyclohexane. In the case of water, the initial and final number of hydrogen bonds of the foldamer with water molecules is found to be unchanged, with no formation of intrachain hydrogen bonding, thus indicating that hydrogen bonding plays no role in the folding process. In all three solvents, the folding is found to be mainly driven by electrostatics, nearly identical in the three cases, and largely dominant compared to van der Waals interactions that are different in the three cases. This scenario is also supported by the analysis of distribution of the bond and dihedral angles and by a direct calculation of the solvation and transfer free energies via thermodynamic integration. The different stability in the case of cyclohexane and n-hexane notwithstanding their rather similar chemical composition can be traced back to the different entropy-enthalpy compensation that is found similar for water and n-hexane, and very different for cyclohexane. A comparison with the same properties for poly-phenylalanine oligomers underscores the crucial differences between pPA and peptides. To highlight how these findings can hardly be interpreted in terms of a simple "good" and "poor" solvent picture, a molecular dynamics study of a bead-spring polymer chain in a Lennard-Jones fluid is also included.

Development and in vitro evaluation of ursolic acid-loaded poly(lactic-co-glycolic acid) nanoparticles in cholangiocarcinoma

Cholangiocarcinoma (CCA), an epithelial biliary tract malignancy, is a significant health concern in the Greater Mekong Subregion, particularly in northeastern Thailand. Prior to the development of advanced stages, CCA is typically asymptomatic, thereby limiting treatment options and chemotherapeutic effectiveness. Ursolic acid (UA), a triterpenoid derived from plants, was previously discovered to inhibit CCA cell growth through induction of apoptosis. Nevertheless, the therapeutic effectiveness of UA is limited by its poor solubility in water and low bioavailability; therefore, dimethyl sulfoxide (DMSO) is utilized as a solvent to treat UA with CCA cells. Enhancing cellular uptake and reducing toxicity, the utilization of polymeric nanoparticles (NPs) proves beneficial. In this study, UA-loaded PLGA nanoparticles (UA-PLGA NPs) were synthesized using nanoprecipitation and characterized through in silico formation analysis, average particle size, surface functional groups and ζ-potential measurements, electron microscopic imaging, drug loading efficiency and drug release studies, stability, hemo- and biocompatibility, cytotoxicity and cellular uptake assays. Molecular dynamics simulations validated the loading of UA into PLGA via hydrogen bonding. The synthesized UA-PLGA NPs had a spherical shape with an average size of 240 nm, a negative ζ-potential, good stability, great hemo- and bio-compatibility and an encapsulation efficiency of 98%. The NPs exhibited a characteristic of a simple diffusion-controlled Fickian process, as predicted by the Peppas-Sahlin drug release kinetic model. UA-PLGA NPs exhibited cytotoxic effects on KKU-213A and KKU-055 CCA cells even when dispersed in media without organic solvent, i.e., DMSO, highlighting the ability of PLGA NPs to overcome the poor water solubility of UA. Rhodamine 6G (R6G) was loaded into PLGA NPs using the same approach as UA-PLGA NPs, demonstrating effective delivery of the dye into CCA cells. These findings suggest that UA-PLGA NPs showed promise as a potential phytochemical delivery system for CCA treatment.

Development of protease resistant and non-cytotoxic Jelleine analogs with enhanced broad spectrum antimicrobial efficacy

Short systemic half- life of Antimicrobial Peptides (AMP) is one of the major bottlenecks that limits their successful commercialization as therapeutics. In this work, we have designed analogs of the natural AMP Jelleine, obtained from royal jelly of apis mellifera. Among the designed peptides, J3 and J4 were the most potent with broad spectrum activities against a varied class of ESKAPE pathogens and fungus C. albicans. All the developed peptides were more effective against Gram-negative bacteria in comparison to the Gram-positive pathogens, and were especially effective against P. aeruginosa and C. albicans.J3 and J4 were completely trypsin resistant and serum stable, while retaining the non-cytotoxicity of the parent Jelleine, Jc. The designed peptides were membranolytic in their mode of action. CD and MD simulations in the presence of bilayers, established that J3 and J4 were non-structured even upon membrane binding and suggested that biological properties of the AMPs were innocent of any specific secondary structural requirements. Enhancement of charge to increase the antimicrobial potency, controlling the hydrophobic-hydrophilic balance to maintain non-cytotoxicity and induction of unnatural amino acid residues to impart protease resistance, remains some of the fundamental principles in the design of more effective antimicrobial therapeutics of the future, which may help combat the quickly rising menace of antimicrobial resistance in the microbes.

Formation of Polyimide Membranes via Non-Solvent Induced Phase Separation: Insight from Molecular Dynamics Simulations

Molecular dynamics simulations were applied to investigate the formation of P84 polyimide membranes through the non-solvent induced phase separation (NIPS) process, considering two scenarios: one using a conventional organic solvent like n-methyl-2-pyrrolidone (NMP) and the other a greener alternative, γ-butyrolactone (GBL), with water serving as the non-solvent. Different compositions of polymer solutions were established along the binodal boundaries of the respective systems, derived from experimental cloud point data on the ternary phase diagram. The resulting polymer membranes were analyzed and compared in terms of their morphology. The wettability of their surfaces was notably affected by the polymer content in the initial casting solution and demonstrated a correlation with the Brunauer-Emmet-Teller (BET) specific surface area of the associated polymer nanostructures. The GBL solvent systems produced porous polymers qualitatively similar to those obtained with NMP, albeit with slightly narrower pore size distributions.

Interactions of a Novel Anthracycline with Oligonucleotide DNA and Cyclodextrins in an Aqueous Environment

Berubicin, a chemotherapy medication belonging to the class of anthracyclines, is simulated in double-stranded DNA sequences and cyclodextrins in an aqueous environment via full-atom molecular dynamics simulations on the time scale of microseconds. The drug is studied in both the neutral and protonated states so as to better comprehend the role of its charge in the formed complexes. The noncovalent berubicin-DNA and berubicin-cyclodextrin complexes are investigated in detail, paying special attention to their thermodynamic description by employing the double decoupling method, the solvent balance method, the weighted solvent accessible surface model, and the linear interaction energy method. A novel approach for extracting the desolvation thermodynamics of the binding process is also presented. Both the binding and desolvation Gibbs energies are decomposed into entropic and enthalpic contributions so as to elucidate the nature of complexation and its driving forces. Selected structural and geometrical properties of all the complexes, which are all stable, are analyzed. Both cyclodextrins under consideration are widely utilized for drug delivery purposes, and a comparative investigation between their bound states with berubicin is carried out.

Essential dynamics of ubiquitin in water and in a natural deep eutectic solvent

Natural deep eutectic solvents (NADESs) comprised of osmolytes are of interest as potential biomolecular (cryo)protectants. However, the way these solvents influence the structure and dynamics of biomolecules as well as the role of water remains poorly understood. We carried out principal component analysis of various secondary structure elements of ubiquitin in water and a betaine : glycerol : water (1 : 2 : ζ; ζ = 0, 1, 2, 5, 10, 20, 45) NADES, from molecular dynamics trajectories, to gain insight into the protein dynamics as it undergoes a transition from a highly viscous anhydrous to an aqueous environment. A crossover of the protein's essential dynamics at ζ ∼ 5, induced by solvent-shell coupled fluctuations, is observed, indicating that ubiquitin might (re)fold in the NADES upon water addition at ζ > ∼5. Further, in contrast to water, the anhydrous NADES preserves ubiquitin's essential modes at high temperatures explaining the protein's seemingly enhanced thermal stability.

Structural Adaptation of Secondary p53 Binding Sites on MDM2 and MDMX

The thermodynamics of secondary p53 binding sites on MDM2 and MDMX were evaluated using p53 peptides containing residues 16-29, 17-35, and 1-73. All the peptides had large, negative heat capacity (ΔCp), consistent with the burial of p53 residues F19, W23, and L26 in the primary binding sites of MDM2 and MDMX. MDMX has a higher affinity and more negative ΔCp than MDM2 for p5317-35, which is due to MDMX stabilization and not additional interactions with the secondary binding site. ΔCp measurements show binding to the secondary site is inhibited by the disordered tails of MDM2 for WT p53 but not a more helical mutant where proline 27 is changed to alanine. This result is supported by all-atom molecular dynamics simulations showing that p53 residues 30-35 turn away from the disordered tails of MDM2 in P27A17-35 and make direct contact with this region in p5317-35. Molecular dynamics simulations also suggest that an intramolecular methionine-aromatic motif found in both MDM2 and MDMX structurally adapts to support multiple p53 binding modes with the secondary site. ΔCp measurements also show that tighter binding of the P27A mutant to MDM2 and MDMX is due to increased helicity, which reduces the energetic penalty associated with coupled folding and binding. Our results will facilitate the design of selective p53 inhibitors for MDM2 and MDMX.

Microphase Separation Produces Interfacial Environment within Diblock Biomolecular Condensates

The phase separation of intrinsically disordered proteins is emerging as an important mechanism for cellular organization. However, efforts to connect protein sequences to the physical properties of condensates, i.e., the molecular grammar, are hampered by a lack of effective approaches for probing high-resolution structural details. Using a combination of multiscale simulations and fluorescence lifetime imaging microscopy experiments, we systematically explored a series of systems consisting of diblock elastin-like polypeptides (ELP). The simulations succeeded in reproducing the variation of condensate stability upon amino acid substitution and revealed different microenvironments within a single condensate, which we verified with environmentally sensitive fluorophores. The interspersion of hydrophilic and hydrophobic residues and a lack of secondary structure formation result in an interfacial environment, which explains both the strong correlation between ELP condensate stability and interfacial hydrophobicity scales, as well as the prevalence of protein-water hydrogen bonds. Our study uncovers new mechanisms for condensate stability and organization that may be broadly applicable.

Data on molecular docking and molecular dynamics targeting Mycobacterium tuberculosis shikimic acid kinase

We have previously performed a hierarchical in silico screening of a Mycobacterium tuberculosis shikimic acid kinase [1]. Specifically, 11 compounds were screened from a library of 154,118 compounds provided by ChemBridge [2] using UCSF DOCK [3] and the GOLD [4] program in the first and second steps, respectively. Molecular dynamic simulations were further performed on compound 2 (2-[(5Z)-5-(1-benzyl-5bromo-2-oxoindol-3-(5Z)-5-(1-benzyl-5-bromo-2-oxoindol-3-(5Z)-4-oxo-2 ylidene)-4oxo-2-sulfanylidene-1,3-thiazolidin-3-yl] acetic acid), which showed antimicrobial efficacy. These processes yielded ligand docking scores and trajectories. In this data article, we have added solvent-accessible surface area and PCA analyses, which were calculated from the raw docking scores and trajectories. Data obtained from molecular docking and molecular dynamic simulations are useful in two ways: (1) Further support for previous work (2) Provides a stepping stone for experimental scientists to conduct in silico studies and research ideas for other drug discovery researchers and computational biologists. We believe that this article will provide an opportunity to develop new Mycobacterium tuberculosis therapeutics through searching for analogs and inhibitors against new targets.

Structure of the human KMN complex and implications for regulation of its assembly

Biorientation of chromosomes during cell division is necessary for precise dispatching of a mother cell's chromosomes into its two daughters. Kinetochores, large layered structures built on specialized chromosome loci named centromeres, promote biorientation by binding and sensing spindle microtubules. One of the outer layer main components is a ten-subunit assembly comprising Knl1C, Mis12C and Ndc80C (KMN) subcomplexes. The KMN is highly elongated and docks on kinetochores and microtubules through interfaces at its opposite extremes. Here, we combine cryogenic electron microscopy reconstructions and AlphaFold2 predictions to generate a model of the human KMN that reveals all intra-KMN interfaces. We identify and functionally validate two interaction interfaces that link Mis12C to Ndc80C and Knl1C. Through targeted interference experiments, we demonstrate that this mutual organization strongly stabilizes the KMN assembly. Our work thus reports a comprehensive structural and functional analysis of this part of the kinetochore microtubule-binding machinery and elucidates the path of connections from the chromatin-bound components to the force-generating components.

Effect of Pressure on the Conformational Landscape of Human γD-Crystallin from Replica Exchange Molecular Dynamics Simulations

Human γD-crystallin belongs to a crucial family of proteins known as crystallins located in the fiber cells of the human lens. Since crystallins do not undergo any turnover after birth, they need to possess remarkable thermodynamic stability. However, their sporadic misfolding and aggregation, triggered by environmental perturbations or genetic mutations, constitute the molecular basis of cataracts, which is the primary cause of blindness in the globe according to the World Health Organization. Here, we investigate the impact of high pressure on the conformational landscape of wild-type HγD-crystallin using replica exchange molecular dynamics simulations augmented with principal component analysis. We find pressure to have a modest impact on global measures of protein stability, such as root-mean-square displacement and radius of gyration. Upon projecting our trajectories along the first two principal components from principal component analysis, however, we observe the emergence of distinct free energy basins at high pressures. By screening local order parameters previously shown or hypothesized as markers of HγD-crystallin stability, we establish correlations between a tyrosine-tyrosine aromatic contact within the N-terminal domain and the protein's end-to-end distance with projections along the first and second principal components, respectively. Furthermore, we observe the simultaneous contraction of the hydrophobic core and its intrusion by water molecules. This exploration sheds light on the intricate responses of HγD-crystallin to elevated pressures, offering insights into potential mechanisms underlying its stability and susceptibility to environmental perturbations, crucial for understanding cataract formation.

Discovery of a New Class of Lipophilic Pyrimidine-Biphenyl Herbicides Using an Integrated Experimental-Computational Approach

Herbicides are useful tools for managing weeds and promoting food production and sustainable agriculture. In this study, we report on the development of a novel class of lipophilic pyrimidine-biphenyl (PMB) herbicides. Firstly, three PMBs, Ia, IIa, and IIIa, were rationally designed via a scaffold hopping strategy and were determined to inhibit acetohydroxyacid synthase (AHAS). Computational simulation was carried out to investigate the molecular basis for the efficiency of PMBs against AHAS. With a rational binding mode, and the highest in vitro as well as in vivo potency, Ia was identified as a preferable hit. Furthermore, these integrated analyses guided the design of eighteen new PMBs, which were synthesized via a one-step Suzuki-Miyaura cross-coupling reaction. These new PMBs, Iba-ic, were more effective in post-emergence control of grass weeds compared with Ia. Interestingly, six of the PMBs displayed 98-100% inhibition in the control of grass weeds at 750 g ai/ha. Remarkably, Ica exhibited ≥ 80% control against grass weeds at 187.5 g ai/ha. Overall, our comprehensive and systematic investigation revealed that a structurally distinct class of lipophilic PMB herbicides, which pair excellent herbicidal activities with new interactions with AHAS, represent a noteworthy development in the pursuit of sustainable weed control solutions.

Structural Rearrangements of Pigeon Cryptochrome 4 Undergoing a Complete Redox Cycle

Cryptochrome is currently the major contender of a protein to underpin magnetoreception, the ability to sense the Earth's magnetic field. Among various types of cryptochromes, cryptochrome 4 has been identified as the likely magnetoreceptor in migratory birds. All-atom molecular dynamics (MD) studies have offered first insights into the structural dynamics of cryptochrome but are limited to a short time scale due to large computational demands. Here, we employ coarse-grained MD simulations to investigate the emergence of long-lived states and conformational changes in pigeon cryptochrome 4. Our coarse-grained simulations complete the picture by permitting observation on a significantly longer time scale. We observe conformational transitions in the phosphate-binding loop of pigeon cryptochrome 4 upon activation and identify prominent motions in residues 440-460, suggesting a possible role as a signaling state of the protein or as a gated interaction site for forming protein complexes that might facilitate downstream processes. The findings highlight the importance of considering longer time scales in studying cryptochrome dynamics and magnetoreception. Coarse-grained MD simulations offer a valuable tool to unravel the complex behavior of cryptochrome proteins and shed new light on the mechanisms underlying their role in magnetoreception. Further exploration of these conformational changes and their functional implications may contribute to a deeper understanding of the molecular mechanisms of magnetoreception in birds.

Effect of ionic groups on the morphology and transport properties in a novel perfluorinated ionomer containing sulfonic and phosphonic acid groups: a molecular dynamics study

Combining the phosphonic acid group with the sulfonic acid group in PEMs has been shown to be an effective strategy for improving the fuel cell performance. However, the interplay of two different ionic groups and the resulting effect on the membrane properties have not been fully elucidated. Here, we used classical molecular dynamics simulation to investigate the morphologies, transport properties and effects of ionic groups in a novel perfluorinated PEM containing two ionic groups (PFSA-PFPA) in comparison to the corresponding homopolymers. Phase separations between hydrophilic and hydrophobic domains are confirmed in these PEMs and result from the evolution of water clusters formed around the ionic groups. The combination of both ionic groups brings a complicated morphological feature in PFSA-PFPA, with near-cylindrical aqueous domains of large length scales interconnected by tortuous domains of small sizes. And we found that the self-diffusion coefficients of water molecules are strongly related to morphologies, with the water transport in PFSA-PFPA lying between two analogous homopolymers. At the molecular level, we found that the sulfonic and phosphonic acid groups have distinct effects on the coordination behaviors and the dynamics of water molecules and hydronium ions. Strong electrostatic interactions lead to compact coordination structures and sluggish dynamics of hydronium ions around phosphonic acid groups, which determine the morphological evolution and transport properties in PFSA-PFPA. Our study affords insights into the relationship between molecular characteristics and transport properties bridged by phase-separated morphologies in a novel PEM containing both sulfonic acid and phosphonic acid groups, which deepens the understanding of the interplay between two ionic groups and may inspire the rational design of high-performance PEMs.

How ATP suppresses the fibrillation of amyloid peptides: analysis of the free-energy contributions

Recent experiments have revealed that adenosine triphosphate (ATP) suppresses the fibrillation of amyloid peptides - a process closely linked to neurodegenerative diseases such as Alzheimer's and Parkinson's. Apart from the adsorption of ATP onto amyloid peptides, the molecular understanding is still limited, leaving the underlying mechanism for the fibrillation suppression by ATP largely unclear, especially in regards to the molecular energetics. Here we provide an explanation at the molecular scale by quantifying the free energies using all-atom molecular dynamics simulations. We found that the changes of the free energies due to the addition of ATP lead to a significant equilibrium shift towards monomeric peptides in agreement with experiments. Despite ATP being a highly charged species, the decomposition of the free energies reveals that the van der Waals interactions with the peptide are decisive in determining the relative stabilization of the monomeric state. While the phosphate moiety exhibits strong electrostatic interactions, the compensation by the water solvent results in a minor, overall Coulomb contribution. Our quantitative analysis of the free energies identifies which intermolecular interactions are responsible for the suppression of the amyloid fibril formation by ATP and offers a promising method to analyze the roles of similarly complex cosolvents in aggregation processes.

Molecular modeling of the carbohydrate corona formation on a polyvinyl chloride nanoparticle and its impact on the adhesion to lipid bilayers

The pervasive presence of nanoplastics (NPs) in the environment has gained increasing attention due to their accumulation in living organisms. These emerging contaminants inevitably interact with extracellular polymeric substances along respiratory or gastrointestinal tracts, and diverse organic coating on the surface of NPs, known as bio- or eco-corona, is formed. Although its impact on altering the NP properties and potential cell internalization has been extensively examined, studies on its role in NP partitioning in the cell membrane are elusive yet. In this work, molecular dynamics is used to investigate the formation of chitosan (CT) corona centered on a polyvinyl chloride (PVC) nanoparticle and the uptake of the resulting complex onto lipid membranes. Coarse-grained models compatible with the newly developed Martini 3.0 force field are implemented for the two polymers employing the atomistic properties as targets in the parameterization. The reliability of the coarse-grained polymer models is demonstrated by reproducing the structural properties of the PVC melt and of solvated CT strands, as well as by determining the conformation adopted by the latter at the NP surface. Results show that the spontaneous binding of CT chains of high and intermediate protonation degrees led to the formation of soft and hard corona that modulates the interaction of PVC core with model membranes. The structural changes of the corona adsorbed at the lipid-water interface enable a subsequent transfer of the NP to the center of the saturated lipid membranes and a complete or partial transition to a snorkel conformation depending on the hydrophilic/hydrophobic balance in the CT-PVC complex. Overall, the computational investigation of the coarse-grained model system provides implications for understanding how the eco-corona development influences the uptake and implicit toxicology of NPs.

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

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

SARS-CoV-2 Omicron Subvariants Do Not Differ Much in Binding Affinity to Human ACE2: A Molecular Dynamics Study

The emergence of the variant of concern Omicron (B.1.1.529) of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) exacerbates the COVID-19 pandemic due to its high contagious ability. Studies have shown that the Omicron binds human ACE2 more strongly than the wild type. The prevalence of Omicron in new cases of COVID-19 promotes novel lineages with improved receptor binding affinity and immune evasion. To shed light on this open problem, in this work, we investigated the binding free energy of the receptor binding domain of the Omicron lineages BA.2, BA.2.3.20, BA.3, BA4/BA5, BA.2.75, BA.2.75.2, BA.4.6, XBB.1, XBB.1.5, BJ.1, BN.1, BQ.1.1, and CH.1.1 to human ACE2 using all-atom molecular dynamics simulation and the molecular mechanics Poisson-Boltzmann surface area method. The results show that these lineages have increased binding affinity compared to the BA.1 lineage, and BA.2.75 and BA.2.75.2 subvariants bind ACE2 more strongly than others. However, in general, the binding affinities of the Omicron lineages do not differ significantly from each other. The electrostatic force dominates over the van der Waals force in the interaction between Omicron lineages and human cells. Based on our results, we argue that viral evolution does not further improve the affinity of SARS-CoV-2 for ACE2 but may increase immune evasion.

Calculations of Absolute Free Energies, Enthalpies, and Entropies for Drug Binding

Computer simulation methods can aid in the rational design of drugs aimed at a specific target, typically a protein. The affinity of a drug for its target is given by the free energy of binding. Binding can be further characterized by the enthalpy and entropy changes in the process. Methods exist to determine exact free energies, enthalpies, and entropies that are dependent only on the quality of the potential model and adequate sampling of conformational degrees of freedom. Entropy and enthalpy are roughly an order of magnitude more difficult to calculate than the free energy. This project combines a replica exchange method for enhanced sampling, designed to be efficient for protein-sized systems, with free energy calculations. This approach, replica exchange with dynamical scaling (REDS), uses two conventional simulations at different temperatures so that the entropy can be found from the temperature dependence of the free energy. A third replica is placed between them, with a modified Hamiltonian that allows it to span the temperature range of the conventional replicas. REDS provides temperature-dependent data and aids in sampling. It is applied to the bromodomain-containing protein 4 (BRD4) system. We find that for the force fields used, the free energies are accurate but the entropies and enthalpies are not, with the entropic contribution being too positive. Reproducing the entropy and enthalpy of binding appears to be a more stringent test of the force fields than reproducing the free energy.

Computer-assisted discovery and evaluation of potential ribosomal protein S6 kinase beta 2 inhibitors

S6K2 is an important protein in mTOR signaling pathway and cancer. To identify potential S6K2 inhibitors for mTOR pathway treatment, a virtual screening of 1,575,957 active molecules was performed using PLANET, AutoDock GPU, and AutoDock Vina, with their classification abilities compared. The MM/PB(GB)SA method was used to identify four compounds with the strongest binding energies. These compounds were further investigated using molecular dynamics (MD) simulations to understand the properties of the S6K2/ligand complex. Due to a lack of available 3D structures of S6K2, OmegaFold served as a reliable 3D predictive model with higher evaluation scores in SAVES v6.0 than AlphaFold, AlphaFold2, and RoseTTAFold2. The 150 ns MD simulation revealed that the S6K2 structure in aqueous solvation experienced compression during conformational relaxation and encountered potential energy traps of about 19.6 kJ mol-1. The virtual screening results indicated that Lys75 and Lys99 in S6K2 are key binding sites in the binding cavity. Additionally, MD simulations revealed that the ligands remained attached to the activation cavity of S6K2. Among the compounds, compound 1 induced restrictive dissociation of S6K2 in the presence of a flexible region, compound 8 achieved strong stability through hydrogen bonding with Lys99, compound 9 caused S6K2 tightening, and the binding of compound 16 was heavily influenced by hydrophobic interactions. This study suggests that these four potential inhibitors with different mechanisms of action could provide potential therapeutic options.

Predicting the Structure of Enzymes with Metal Cofactors: The Example of [FeFe] Hydrogenases

The advent of deep learning algorithms for protein folding opened a new era in the ability of predicting and optimizing the function of proteins once the sequence is known. The task is more intricate when cofactors like metal ions or small ligands are essential to functioning. In this case, the combined use of traditional simulation methods based on interatomic force fields and deep learning predictions is mandatory. We use the example of [FeFe] hydrogenases, enzymes of unicellular algae promising for biotechnology applications to illustrate this situation. [FeFe] hydrogenase is an iron-sulfur protein that catalyzes the chemical reduction of protons dissolved in liquid water into molecular hydrogen as a gas. Hydrogen production efficiency and cell sensitivity to dioxygen are important parameters to optimize the industrial applications of biological hydrogen production. Both parameters are related to the organization of iron-sulfur clusters within protein domains. In this work, we propose possible three-dimensional structures of Chlorella vulgaris 211/11P [FeFe] hydrogenase, the sequence of which was extracted from the recently published genome of the given strain. Initial structural models are built using: (i) the deep learning algorithm AlphaFold; (ii) the homology modeling server SwissModel; (iii) a manual construction based on the best known bacterial crystal structure. Missing iron-sulfur clusters are included and microsecond-long molecular dynamics of initial structures embedded into the water solution environment were performed. Multiple-walkers metadynamics was also used to enhance the sampling of structures encompassing both functional and non-functional organizations of iron-sulfur clusters. The resulting structural model provided by deep learning is consistent with functional [FeFe] hydrogenase characterized by peculiar interactions between cofactors and the protein matrix.

Electric field induced the changes in structure and function of human transforming growth factor beta receptor type I: from molecular dynamics to docking

The transforming growth factor beta (TGF-β) signaling pathway is believed to play essential roles in several physiological activities, including cancer. TGF-β receptor type I (TBR-I) is a key membrane receptor protein in the TGF-β signaling pathway, which relates to many intracellular biological effects. In recent years, cold atmospheric plasma (CAP) has been found to have promising prospects in selective anticancer therapy and has confirmed its essential role in the TGF-β signaling pathway. However, the ambiguous effect of CAP-induced electric field (EF) on TBR-I still limits the application of CAP in clinical therapy. Molecular dynamics is applied to assess the effect of EF on the structure of the extracellular domain of TBR-I using a series of indicators and methods, and then we discuss the ligand binding ability of TBR-I. Results show that moderate EF intensities' structural restraints may contribute to the structural stability and ligand-binding ability of TBR-I, but an EF higher than 0.1 V/nm will be harmful. What's more, EF induces a change in the docking interface of TBR-I, showing the conformation and position of special sequences of residues decide the ligand binding surface. The relevant results suggest that CAP-induced EF plays a crucial role in receptor-receptor interaction and provides significant guidelines for EF-related anticancer therapy.Communicated by Ramaswamy H. Sarma.

Unraveling Partial Coalescence Between Droplet and Oil-Water Interface in Water-in-Oil Emulsions under a Direct-Current Electric Field via Molecular Dynamics Simulation

When the electric field strength (E) surpasses a certain threshold, secondary droplets are generated during the coalescence between water droplets in oil and the oil-water interface (so-called the droplet-interface partial coalescence phenomenon), resulting in a lower efficiency of droplet electrocoalescence. This study employs molecular dynamics (MD) simulations to investigate the droplet-interface partial coalescence phenomenon under direct current (DC) electric fields. The results demonstrate that intermolecular interactions, particularly the formation of hydrogen bonds, play a crucial role in dipole-dipole coalescence. Droplet-interface partial coalescence is categorized into five regimes based on droplet morphology. During the contact and fusion of the droplet with the water layer, the dipole moment of the droplet exhibits alternating increases and decreases along the electric field direction. Electric field forces acting on sodium ions and the internal interactions within droplets promote the process of droplet-interface partial coalescence. High field strengths cause significant elongation of the droplet, leading to its fragmentation into multiple segments. The migration of hydrated ions has a dual impact on the droplet-interface partial coalescence, with both facilitative and suppressive effects. The time required for droplet-interface partial coalescence initially decreases and subsequently increases as the field strength increases, depending on the competitive relationship between the extent of droplet stretching and the electric field force. This work provides molecular insights into the droplet-interface coalescence mechanisms in water-in-oil emulsions under DC electric fields.

Structural studies of catalytic peptides using molecular dynamics simulations

Many self-assembling peptides can form amyloid like structures with different sizes and morphologies. Driven by non-covalent interactions, their aggregation can occur through distinct pathways. Additionally, they can bind metal ions to create enzyme like active sites that allow them to catalyze diverse reactions. Due to the non-crystalline nature of amyloids, it is quite challenging to elucidate their structures using experimental spectroscopic techniques. In this aspect, molecular dynamics (MD) simulations provide a useful tool to derive structures of these macromolecules in solution. They can be further validated by comparing with experimentally measured structural parameters. However, these simulations require a multi-step process starting from the selection of the initial structure to the analysis of MD trajectories. There are multiple force fields, parametrization protocols, equilibration processes, software and analysis tools available for this process. Therefore, it is complicated for non-experts to select the most relevant tools and perform these simulations effectively. In this chapter, a systematic methodology that covers all major aspects of modeling of catalytic peptides is provided in a user-friendly manner. It will be helpful for researchers in this critical area of research.

Mechanistic Insights into the Adsorption of Monoclonal Antibodies at the Water/Vapor Interface

Monoclonal antibodies (mAbs) are active components of therapeutic formulations that interact with the water-vapor interface during manufacturing, storage, and administration. Surface adsorption has been demonstrated to mediate antibody aggregation, which leads to a loss of therapeutic efficacy. Controlling mAb adsorption at interfaces requires a deep understanding of the microscopic processes that lead to adsorption and identification of the protein regions that drive mAb surface activity. Here, we report all-atom molecular dynamics (MD) simulations of the adsorption behavior of a full IgG1-type antibody at the water/vapor interface. We demonstrate that small local changes in the protein structure play a crucial role in promoting adsorption. Also, interfacial adsorption triggers structural changes in the antibody, potentially contributing to the further enhancement of surface activity. Moreover, we identify key amino acid sequences that determine the adsorption of antibodies at the water-air interface and outline strategies to control the surface activity of these important therapeutic proteins.

Effect of ligand and shell densities on the surface structure of core-shell nanoparticles self-assembled from function-spacer-lipid constructs

Biomolecular corona is the major obstacle to the clinical translation of nanomedicines. Since corona formation is governed by molecular interactions at the nano-bio interface, nanoparticle surface properties such as topography, charge and surface chemistry can be tuned to manipulate biomolecular corona formation. To this end, as the first step towards a deep understanding of the processes of corona formation, it is necessary to develop nanoparticles employing various biocompatible materials and characterize their surface structure and dynamics at the molecular level. In this work, we applied molecular dynamics simulation to study the surface structure of organic core-shell nanoparticles formed by the self-assembly of synthetic molecules composed of a DOPE lipid, a carboxymethylglycine spacer and biotin. Lipid moieties form the hydrophobic core, spacer motifs serve as a hydrophilic shell and biotin residues function as a targeting ligand. By mixing such function-spacer-lipid, spacer-lipid and lipid-only constructs at various molar ratios, densities of the ligand and spacer on the nanoparticle surface were modified. For convenient analysis of the structure and dynamics of all regions of the nanoparticle surface, we compiled topography maps based on atomic coordinates. It was shown that an increase in the density of the shell does not reduce exposure of the core, but increases shell average thickness. Biotin, due to its alkyl valeric acid chain and spacer flexibility, is localized primarily near the hydrophobic core and its partial presentation on the surface occurs only in nanoparticles with higher ligand densities. However, an increase in biotin density leads to its clustering. In turn, ligand clustering diminishes the stealth properties of the shell and targeting efficiency. Based on nanoparticle surface structures, we determined the optimal density of biotin. Experimental studies reported in the literature confirm these conclusions. We also suggest design tips to achieve the preferred biotin presentation. Simulation results are consistent with the synchrotron SAXS profile. We believe that such studies will contribute to a better understanding of nano-bio interactions towards the rational design of efficient drug delivery systems.

Identification of apigenin-4'-glucoside as bacterial DNA gyrase inhibitor by QSAR modeling, molecular docking, DFT, molecular dynamics, and in vitro confirmation studies

CONTEXT

It is well known that antibiotic resistance is a major health hazard. To eradicate antibiotic-resistant bacterial infections, it is essential to find a novel antibacterial agent. Hence, in this study, a quantitative structure-activity relationship (QSAR) model was developed using 43 DNA gyrase inhibitors, and 700 natural compounds were screened for their antibacterial properties. Based on molecular docking and absorption, distribution, metabolism, excretion, and toxicity (ADMET) studies, the top three leads viz., apigenin-4'-glucoside, 8-deoxygartanin, and cryptodorine were selected and structurally optimized using density functional theory (DFT) studies. The optimized structures were redocked, and molecular dynamic (MD) simulations were performed. Binding energies were calculated by molecular mechanics/Poisson-Boltzmann surface area solvation (MM-PBSA). Based on the above studies, apigenin-4'-glucoside was identified as a potent antibacterial lead. Further in vitro confirmation studies were performed using the plant Lawsonia inermis containing apigenin-4'-glucoside to confirm the antibacterial activity.

METHODS

For QSAR modeling, 2D descriptors were calculated by PaDEL-Descriptors v2.21 software, and the model was developed using the DTClab QSAR tool. Docking was performed using PyRx v0.8 software. ORCA v5.0.1 computational package was used to optimize the structures. The job type used in optimization was equilibrium structure search using the DFT hybrid functional ORCA method B3LYP. The basis set was 6-311G (3df, 3pd) plus four polarization functions for all atoms. Accurate docking was performed for optimized leads using the iGEMDOCK v2.1 tool with a genetic algorithm by 10 solutions each of 80 generations. Molecular dynamic simulations were performed using GROMACS 2020.04 software with CHARMM36 all-atom force field.

Techniques for Developing Reliable Machine Learning Classifiers Applied to Understanding and Predicting Protein:Protein Interaction Hot Spots

With machine learning now transforming the sciences, successful prediction of biological structure or activity is mainly limited by the extent and quality of data available for training, the astute choice of features for prediction, and thorough assessment of the robustness of prediction on a variety of new cases. In this chapter, we address these issues while developing and sharing protocols to build a robust dataset and rigorously compare several predictive classifiers using the open-source Python machine learning library, scikit-learn. We show how to evaluate whether enough data has been used for training and whether the classifier has been overfit to training data. The most telling experiment is 500-fold repartitioning of the training and test sets, followed by prediction, which gives a good indication of whether a classifier performs consistently well on different datasets. An intuitive method is used to quantify which features are most important for correct prediction.The resulting well-trained classifier, hotspotter, can robustly predict the small subset of amino acid residues on the surface of a protein that are energetically most important for binding a protein partner: the interaction hot spots. Hotspotter has been trained and tested here on a curated dataset assembled from 1046 non-redundant alanine scanning mutation sites with experimentally measured change in binding free energy values from 97 different protein complexes; this dataset is available to download. The accessible surface area of the wild-type residue at a given site and its degree of evolutionary conservation proved the most important features to identify hot spots. A variant classifier was trained and validated for proteins where only the amino acid sequence is available, augmented by secondary structure assignment. This version of hotspotter requiring fewer features is almost as robust as the structure-based classifier. Application to the ACE2 (angiotensin converting enzyme 2) receptor, which mediates COVID-19 virus entry into human cells, identified the critical hot spot triad of ACE2 residues at the center of the small interface with the CoV-2 spike protein. Hotspotter results can be used to guide the strategic design of protein interfaces and ligands and also to identify likely interfacial residues for protein:protein docking.

Solvent-Assisted Graphene Exfoliation from Graphite Using Umbrella Sampling Simulations

We employed molecular dynamics (MD) simulations coupled with umbrella sampling to explore the thermodynamics governing the exfoliation of a single graphene layer from a graphitic substrate in five different solvents such as dimethylacetamide (DMA), N-methyl-2-pyrrolidone (NMP), dimethyl sulfoxide (DMSO), cyclohexane (CHX), and water. The substrate was modeled as a stack of three identical graphene layers with the graphene sheet undergoing exfoliation positioned on top of this stack. The initial configurations for each umbrella simulation were generated through steered MD simulations carried out along two distinct coordinates: one parallel and the other perpendicular to the graphene layers. Our analyses revealed a uniform wetting behavior for both the nanosheet and the graphitic substrate in all of the tested solvents. Consistent with experimental observations, the steered simulations confirmed that exfoliation is more favorable along the parallel direction than along the perpendicular one. All non-water solvents exhibit comparable effectiveness in the exfoliation of graphene. The calculated free energies of these solvents in parallel exfoliation consistently fell within the range of 90-100 kJ/mol/nm2. In perpendicular exfoliation, however, the corresponding energies converge to lower values. This difference is attributed to the nonequilibrium nature of the perpendicular exfoliation, primarily caused by the great steering velocity of the graphene sheet immediately after detachment from the substrate. This rapid motion of the nanosheet along the perpendicular coordinate results in an elevated system energy and heating.

Classification of Hemilabile Ligands Using Machine Learning

Hemilabile ligands have the capacity to partially disengage from a metal center, providing a strategy to balance stability and reactivity in catalysis, but they are not straightforward to identify. We identify ligands in the Cambridge Structural Database that have been crystallized with distinct denticities and are thus identifiable as hemilabile ligands. We implement a semi-supervised learning approach using a label-spreading algorithm to augment a small negative set that is supported by heuristic rules of ligand and metal co-occurrence. We show that a heuristic based on coordinating atom identity alone is not sufficient to identify whether a ligand is hemilabile, and our trained machine-learning classification models are instead needed to predict whether a bi-, tri-, or tetradentate ligand is hemilabile with high accuracy and precision. Feature importance analysis of our models shows that the second, third, and fourth coordination spheres all play important roles in ligand hemilability.

Accurate and Efficient SAXS/SANS Implementation Including Solvation Layer Effects Suitable for Molecular Simulations

Small-angle X-ray and neutron scattering (SAXS/SANS) provide valuable insights into the structure and dynamics of biomolecules in solution, complementing a wide range of structural techniques, including molecular dynamics simulations. As contrast-based methods, they are sensitive not only to structural properties but also to solvent-solute interactions. Their use in molecular dynamics simulations requires a forward model that should be as fast and accurate as possible. In this work, we demonstrate the feasibility of calculating SAXS and SANS intensities using a coarse-grained representation consisting of one bead per amino acid and three beads per nucleic acid, with form factors that can be corrected on the fly to account for solvation effects at no additional computational cost. By coupling this forward model with molecular dynamics simulations restrained with SAS data, it is possible to determine conformational ensembles or refine the structure and dynamics of proteins and nucleic acids in agreement with the experimental results. To assess the robustness of this approach, we applied it to gelsolin, for which we acquired SAXS data on its closed state, and to a UP1-microRNA complex, for which we used previously collected measurements. Our hybrid-resolution small-angle scattering (hySAS) implementation, being distributed in PLUMED, can be used with atomistic and coarse-grained simulations using diverse restraining strategies.

In silico and structure-based assessment to classify VUS identified in the α-helical domain of BRCA2

Breast cancer type 2 susceptibility (BRCA2) protein plays a crucial role in DNA double-strand breaks repair mechanism by homologous recombination. Pathogenic mutations in the BRCA2 gene confer an increased risk of hereditary breast and ovarian cancer (HBOC). Different missense mutations are identified from a larger cohort of patient populations in the BRCA2. However, most missense mutations are classified as 'Variants of Uncertain Significance' (VUS) due to a lack of data from structural, functional, and clinical assessments. Therefore, this study focused on assessing VUS identified in the α-helical domain of h-BRCA2 using different in silico tools and structure-based molecular dynamics simulation. A total of 286 identified VUS were evaluated using Align-GVGD, PROVEAN and PANTHER servers and 18 variants were predicted to be pathogenic. Further, out of 18 variants analyzed using the ConSurf server, 16 variants were found to be evolutionary conserved. These 16 conserved variants were submitted to PremPS and Dynamut server to assess the effect of the mutation at the protein structure level; 12 mutations were predicted to have a destabilizing effect on the native protein structure. Finally, molecular dynamics simulations revealed 5 variants BRCA2 Cys2646Tyr, Asp2665Val, Trp2619Arg, Trp2619Ser and Tyr2660Cys can alter the folding pattern and need further validation using in vitro, structural and in vivo studies to classify as pathogenic.Communicated by Ramaswamy H. Sarma.

Molecular dynamics simulation study on Bacillus subtilis EngA: the presence of Mg2+ at the active-sites promotes the functionally important conformation

EngA, a GTPase contains two GTP binding domains [GD1, GD2], and the C-terminal KH domain shown to be involved in the later stages of ribosome maturation. Association of EngA to the ribosomal subunit in the intermediate stage of maturation is essential for complete ribosome maturation. However, this association was shown to be dependent on the nucleotide bound combinations. This nucleotide dependent association tendency is attributed to the conformational changes that occur among different nucleotide bound combinations. Therefore, to explore the conformational changes, all-atom molecular dynamics simulations for Bacillus subtilis EngA in different nucleotide bound combinations along with the presence or absence of Mg2+ in the active-sites were carried out. The presence of Mg2+ along with the bound nucleotide at the GD2 active-site dictates the GD2-Sw-II mobility, but the GD1-Sw-II mobility has not shown any nucleotide or Mg2+ dependent movement. However, the GD1-Sw-II secondary conformations are shown to be influenced by the GD2 nucleotide bound state. This allosteric connection between the GD2 active-site and the GD1-Sw-II is also observed through the dynamic network analysis. Further, the exploration of the GD1-KH interface interactions exhibited a more attractive tendency when GD1 is bound to GTP-Mg2+. In addition, the presence of Mg2+ stabilizes active-site water and also increases the distances between the α- and γ- phosphates of the bound GTP. Curiously, three water molecules in the GD1 active-site and only one water molecule in the GD2 active-site are stabilized. This indicates that the probability of GTP hydrolysis is more in GD1 compared to GD2.Communicated by Ramaswamy H. Sarma.

The C-terminal tail of Rad17, iVERGE, binds the 9‒1‒1 complex independently of AAA+ ATPase domains to provide another clamp-loader interface

The ATR pathway plays a crucial role in maintaining genome integrity as the major DNA damage checkpoint. It also attracts attention as a therapeutic target in cancer treatment. The Rad17-RFC2-5 complex loads the Rad9-Hus1-Rad1 (9-1-1) DNA clamp complex onto damaged chromatin to activate the ATR pathway. We previously reported that phosphorylation of a polyanionic C-terminal tail of human Rad17, iVERGE, is essential for the interaction between Rad17 and the 9-1-1 complex. However, the molecular mechanism has remained unclear. Here, we show that iVERGE directly interacts with the Hus1 subunit of the 9-1-1 complex through Rad17-S667 phosphorylation independently of the AAA+ ATPase domains. An exogenous iVERGE peptide interacted with the 9-1-1 complex in vivo. The binding conformation of the iVERGE peptide was analyzed by de novo modeling with docking simulation, simulated annealing-molecular dynamics simulation, and the fragment molecular orbital method. The in silico analyses predicted the association of the iVERGE peptide with the hydrophobic and basic patches on the Hus1 protein, and the corresponding Hus1 mutants were deficient in the interaction with the iVERGE peptide in vivo. The iVERGE peptide occupied the same position as the C-terminus of Saccharomyces cerevisiae RAD24 on MEC3. The interaction energy calculation suggested that the Rad17 KYxxL motif and the iVERGE peptide are the primary and secondary interaction surfaces between the Rad17-RFC2-5 and 9-1-1 complexes. Our data reveal a novel molecular interface, iVERGE, between the Rad17-RFC2-5 and 9-1-1 complexes in vertebrates and implicate that Rad17 utilizes two distinct molecular interfaces to regulate the 9-1-1 complex.

Computational insights of the molecular recognition between volatile molecules and odorant binding proteins from the red palm weevil Rhynchophorus ferrugineus

The red palm weevil Rhynchophorus ferrugineus (Coleoptera: Curculionidae) is one of the most harmful pests for palm trees, causing serious economic damage worldwide. The present work aims to model and study the 3D structures of highly expressed odorant binding proteins from R. ferrugineus (RferOBPs) and identify possible binding modes and ligand release mechanism by docking and molecular dynamics. Highly confident 3D structures of a total of 11 odorant binding proteins (OBPs) were obtained with AlphaFold2. All 3D RferOBPs modeled structures displayed six characteristic α-helices, except for RfeOBP7 and RfeOBP10, which had an extra terminal α-helix. Among the eleven modeled RferOBPs, RferOBP4 was highly expressed in the antennae and subsequently selected for further analyses. Molecular docking analyses demonstrated that ferruginol, α-pinene, DEET, and picaridin can favorably bind the RferOBP4 cavity with low affinity energies. Molecular dynamic simulations of RferOBP4 bound to ferruginol at different pH values showed that low pH environments dictate a structural change into an apo-state that modifies the number of tunnels where the ligand can coexist, further triggering ligand release by a pH-dependent mechanism. This is the first report concerning the modelling and study of ligand binding modes and release mechanism of R. ferrugineus OBPs.Communicated by Ramaswamy H. Sarma.

CHAPERONg: A tool for automated GROMACS-based molecular dynamics simulations and trajectory analyses

Molecular dynamics (MD) simulation is a powerful computational tool used in biomolecular studies to investigate the dynamics, energetics, and interactions of a wide range of biological systems at the atomic level. GROMACS is a widely used free and open-source biomolecular MD simulation software recognized for its efficiency, accuracy, and extensive range of simulation options. However, the complexity of setting up, running, and analyzing MD simulations for diverse systems often poses a significant challenge, requiring considerable time, effort, and expertise. Here, we introduce CHAPERONg, a tool that automates the GROMACS MD simulation pipelines for protein and protein-ligand systems. CHAPERONg also integrates seamlessly with GROMACS modules and third-party tools to provide comprehensive analyses of MD simulation trajectories, offering up to 20 post-simulation processing and trajectory analyses. It also streamlines and automates established pipelines for conducting and analyzing biased MD simulations via the steered MD-umbrella sampling workflow. Thus, CHAPERONg makes MD simulations more accessible to beginner GROMACS users whilst empowering experts to focus on data interpretation and other less programmable aspects of MD simulation workflows. CHAPERONg is written in Bash and Python, and the source code is freely available at https://github.com/abeebyekeen/CHAPERONg. Detailed documentation and tutorials are available online at dedicated web pages accessible via https://abeebyekeen.com/chaperong-online.

Interaction of SARS-CoV-2 with host cells and antibodies: experiment and simulation

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the causative agent of the devastating global COVID-19 pandemic announced by WHO in March 2020. Through unprecedented scientific effort, several vaccines, drugs and antibodies have been developed, saving millions of lives, but the fight against COVID-19 continues as immune escape variants of concern such as Delta and Omicron emerge. To develop more effective treatments and to elucidate the side effects caused by vaccines and therapeutic agents, a deeper understanding of the molecular interactions of SARS-CoV-2 with them and human cells is required. With special interest in computational approaches, we will focus on the structure of SARS-CoV-2 and the interaction of its spike protein with human angiotensin-converting enzyme-2 (ACE2) as a prime entry point of the virus into host cells. In addition, other possible viral receptors will be considered. The fusion of viral and human membranes and the interaction of the spike protein with antibodies and nanobodies will be discussed, as well as the effect of SARS-CoV-2 on protein synthesis in host cells.