CHARMM36 all-atom additive protein force field: validation based on comparison to NMR data

Analysis of how antigen mutations disrupt antibody binding interactions toward enabling rapid and reliable antibody repurposing

Antibody repurposing is the process of changing a known antibody so that it binds to a mutated antigen. One of the findings to emerge from the Coronavirus Disease 2019 (COVID-19) pandemic was that it was possible to repurpose neutralizing antibodies for Severe Acute Respiratory Syndrome, a related disease, to work for COVID-19. Thus, antibody repurposing is a possible pathway to prepare for and respond to future pandemics, as well as personalizing cancer therapies. For antibodies to be successfully repurposed, it is necessary to know both how antigen mutations disrupt their binding and how they should be mutated to recover binding, with this work describing an analysis to address the first of these topics. Every possible antigen point mutation in the interface of 246 antibody-protein complexes were analyzed using the Rosetta molecular mechanics force field. The results highlight a number of features of how antigen mutations affect antibody binding, including the effects of mutating critical hotspot residues versus other positions, how many mutations are necessary to be likely to disrupt binding, the prevalence of indirect effects of mutations on binding, and the relative importance of changing attractive versus repulsive energies. These data are expected to be useful in guiding future antibody repurposing experiments.

Interfacial interactions between DNA and polysaccharide-coated magnetic nanoparticles: Insight from simulations and experiments

In this work we examine the structural and energetic stability and the interactions between dextran-coated magnetic nanoparticles (MNPs) and a DNA oligonucleotide at ionic strength conditions that are relevant to physiological gene delivery processes. All-atom Molecular Dynamics simulations provided information at the atomic-level regarding the mechanisms responsible for the physical adsorption of Dextran on the magnetic surface and the conditions under which a successful DNA-Dextran complexation can be accomplished. Coulombic interactions were found to play the main role for the formation of the Dextran interfacial layer onto the magnetic surface while hydrogen bonding between the Dextran molecules enhanced the structural integrity of this layer. The Dextran-DNA complexation was also driven by electrostatic interactions between the two moieties. An increase of the salt concentration was found to promote DNA complexation with the DX-coated magnetic nanoparticles, through the modification of the Coulombic interactions between the DX and DNA chains, which worked synergistically with the increase in hydrogen bonding between the two macromolecules. Comparison of the behavior of the coated with the uncoated magnetic nanoparticles, highlighted the significant role of the DX interfacial layer on the DNA association to the magnetic surface. Relevant experimental results provided complementary information for the coated nanoparticle/DNA interactions at different (larger) length scales. A good qualitative agreement was found between the simulation and experimental findings. This study demonstrates that tailoring the nanoparticle coating and ionic strength can optimize the delivery of DNA by fine-tuning the favorable interfacial forces and thus the DNA/MNP binding stability.

Molecular Interactions of the Pioneer Transcription Factor GATA3 With DNA

The GATA3 transcription factor is a pioneer transcription factor that is critical in the development, proliferation, and maintenance of several immune cell types. Identifying the detailed conformational dynamics and interactions of this transcription factor, as well as its clinically important population variants will allow us to unravel its mode of action. In this study, we analyze the molecular interactions of the GATA3 transcription factor bound to dsDNA as well as three clinically important population variants by atomistic molecular dynamics simulations. We identify the effect of the variants on the DNA conformational dynamics and delineate the differences compared to the wildtype transcription factor that could be related to impaired function. We highlight the structural plasticity in the binding of the GATA3 transcription factor and identify important DNA-protein contacts. Although the DNA-protein contacts are persistent and appear to be stable, they exhibit nanosecond timescale fluctuations and several binding/unbinding events. Further, we identify differential DNA binding in the three variants and show that the N-terminal binding is reduced in two of the variants. Our results indicate that reduced minor groove width and DNA diameter are important hallmarks for the binding of GATA3. Our work is an important step towards understanding the functional dynamics of the GATA3 protein and its clinically significant population variants.

The interaction of methotrexate with the human C5a and its potential therapeutic implications

Methotrexate (MTX) is an antimetabolite drug that mimics folate and inhibits dihydrofolic acid reductase, resulting in the impairment of malignant growth in actively proliferating tissues. MTX is approved by the FDA for primarily treating non-Hodgkin lymphoma, lymphoblastic leukemia, and osteosarcoma. In addition, MTX is also prescribed as a preferred anti-rheumatic medication for the management of rheumatoid arthritis, including psoriasis, indicating that MTX has a multipronged mechanism of action. MTX is also known to exert anti-inflammatory effects, and interestingly, the role of C5a, a pro-inflammatory glycoprotein of the complement system, is well established in several chronic inflammatory diseases, including rheumatoid arthritis and psoriasis, through the recruitment of C5a receptors (C5aR1/C5aR2) expressed in both immune and non-immune cells. Notably, through drug repurposing studies, we have earlier shown that non-steroidal anti-inflammatory drugs (NSAIDS) can potentially neutralize the function of C5a. Though MTX binds to serum albumin and can affect the immune system, whether its interaction with C5a could be therapeutically beneficial due to the downregulation of both extracellular and intracellular signaling of C5a is not yet established in the literature. In the current study, we have hypothesized and provided preliminary evidence through computational studies that MTX can strongly bind to the hotspot regions on C5a involved in the interactions with its receptors, which is likely to alter the downstream signaling of C5a and contribute to the overall therapeutic efficacy of MTX.

Additive CHARMM Force Field for Pterins and Folates

Folates comprise a crucial class of biologically active compounds related to folic acid, playing a vital role in numerous enzymatic reactions. One-carbon metabolism, facilitated by the folate cofactor, supports numerous physiological processes, including biosynthesis, amino acid homeostasis, epigenetic maintenance, and redox defense. Folates share a common pterin heterocyclic ring structure capable of undergoing redox reactions and existing in various protonation states. This study aimed to derive molecular mechanics (MM) parameters compatible with the CHARMM36 all-atom additive force field for pterins and biologically important folates, including pterin, biopterin, and folic acid. Three redox forms were considered: oxidized, dihydrofolate, and tetrahydrofolate states. Across all protonation states, a total of 18 folates were parameterized. Partial charges were derived using the CHARMM force field parametrization protocol, based on targeting reference quantum mechanics monohydrate interactions, electrostatic potential, and dipole moment. Bonded terms were parameterized using one-dimensional adiabatic potential energy surface scans, and two-dimensional scans to parametrize in-ring torsions associated with the puckering states of dihydropterin and tetrahydropterin. The quality of the model was demonstrated through simulations of three protein complexes using optimized and initial parameters. These simulations underscored the significantly enhanced performance of the folate model developed in this study compared to the initial model without optimization in reproducing structural properties of folate-protein complexes. Overall, the presented MM model will be valuable for modeling folates in various redox states and serve as a starting point for parameterizing other folate derivatives.

A propofol binding site in the voltage sensor domain mediates inhibition of HCN1 channel activity

Hyperpolarization-activated and cyclic nucleotide-gated (HCN) ion channels are members of the cyclic nucleotide-binding family and are crucial for regulating cellular automaticity in many excitable cells. HCN channel activation contributes to pain perception, and propofol, a widely used anesthetic, acts as an analgesic by inhibiting the voltage-dependent activity of HCN channels. However, the molecular determinants of propofol action on HCN channels remain unknown. Here, we use a propofol-analog photoaffinity labeling reagent to identify propofol binding sites in the human HCN1 isoform. Mass spectrometry analyses combined with molecular dynamics simulations show that a binding pocket is formed by extracellularly facing residues in the S3 and S4 transmembrane segments in the resting voltage-sensor conformation. Mutations of residues within the putative binding pocket mitigate or eliminate voltage-dependent modulation of HCN1 currents by propofol. Together, these findings reveal a conformation-specific propofol binding site that underlies voltage-dependent inhibition of HCN currents and provides a framework for identifying highly specific modulators of HCN channel gating.

Two cooperative lipid binding sites within the pleckstrin homology domain are necessary for AKT binding and stabilization to the plasma membrane

Almost four decades after the identification of the AKT protein and understanding of its role in cancer, barriers remain in the translation of AKT inhibitors for clinical applications. Here, we provide new molecular insight into the first step of AKT activation where AKT binds to the plasma membrane and its orientation is stabilized in a bilayer with lateral heterogeneity (Lo-Ld phase coexistence). We have applied molecular dynamic simulations and molecular and cell biology approaches, and demonstrate that AKT recruitment to the membrane requires a second binding site in the AKT pleckstrin homology (PH) domain that acts cooperatively with the known canonical binding site. Given the precision with which we have identified the protein-lipid interactions, the study offers new directions for AKT-targeted therapy and for testing small molecules to target these specific amino acid-PIP molecular bonds.

Structural insights into the regulation of monomeric and dimeric apelin receptor

The apelin receptor (APJR) emerges as a promising drug target for cardiovascular health and muscle regeneration. While prior research unveiled the structural versatility of APJR in coupling to Gi proteins as a monomer or dimer, the dynamic regulation within the APJR dimer during activation remains poorly understood. In this study, we present the structures of the APJR dimer and monomer complexed with its endogenous ligand apelin-13. In the dimeric structure, apelin-13 binds exclusively to one protomer that is coupled with Gi proteins, revealing a distinct ligand-binding behavior within APJR homodimers. Furthermore, binding of an antagonistic antibody induces a more compact dimerization by engaging both protomers. Notably, structural analyses of the APJR dimer complexed with an agonistic antibody, with or without Gi proteins, suggest that G protein coupling may promote the dissociation of the APJR dimer during activation. These findings underscore the intricate interplay between ligands, dimerization, and G protein coupling in regulating APJR signaling pathways.

Structure-function analyses of human TRPV6 ancestral and derived haplotypes

TRPV6 is a Ca2+ selective channel that mediates calcium uptake in the gut and contributes to the development and progression of human cancers. TRPV6 is represented by the ancestral and derived haplotypes that differ by three non-synonymous polymorphisms, located in the N-terminal ankyrin repeat domain (C157R), S1-S2 extracellular loop (M378V), and C-terminus (M681T). The ancestral and derived haplotypes were proposed to serve as genomic factors causing a different outcome for cancer patients of African ancestry. We solved cryoelectron microscopy (cryo-EM) structures of ancestral and derived TRPV6 in the open and calmodulin (CaM)-bound inactivated states. Neither state shows substantial structural differences caused by the non-synonymous polymorphisms. Functional properties assessed by electrophysiological recordings and Ca2+ uptake measurements, and water and ion permeation evaluated by molecular modeling also appear similar between the haplotypes. Therefore, ancestral and derived TRPV6 have similar structure and function, implying that other factors are responsible for the differences in susceptibility to cancer.

Repurposing Phytochemicals against Breast Cancer (MCF-7) using Classical Structure-Based Drug Design

BACKGROUND

The significant public health effect of breast cancer is demonstrated by its high global prevalence and the potential for severe health consequences. The suppression of the proliferative effects facilitated by the estrogen receptor alpha (ERα) in the MCF-7 cell line is significant for breast cancer therapy.

OBJECTIVE

The current work involves in-silico techniques for identifying potential inhibitors of ERα.

METHODS

The method combines QSAR models based on machine learning with molecular docking to identify potential binders for the ERα. Further, molecular dynamics simulation studied the stability of the complexes, and ADMET analysis validated the compound's properties.

RESULTS

Two compounds (162412 and 443440) showed significant binding affinities with ERα, with binding energies comparable to the established binder RL4. The ADMET qualities showed advantageous characteristics resembling pharmaceutical drugs. The stable binding of these ligands in the active region of ERα during dynamic conditions was confirmed by molecular dynamics simulations. RMSD plots and conformational stability supported the ligands' persistent occupancy in the protein's binding site. After simulation, two hydrogen bonds were found within the protein-ligand complexes of 162412 and 443440, with binding free energy values of -27.32 kcal/mol and -25.00 kcal/mol.

CONCLUSION

The study suggests that compounds 162412 and 443440 could be useful for developing innovative anti-ERα medicines. However, more research is needed to prove the compounds' breast cancer treatment efficacy. This will help develop new treatments for ERα-associated breast cancer.

Insight into the effect of ibuprofen on the permeability of the membrane: a molecular dynamic simulation study

Studying interactions between drugs and cell membranes is of great interest to designing novel drugs, optimizing drug delivery, and discerning drug mechanism action. In this study, we investigated the physical properties of the bilayer membrane model of POPC upon interaction with ibuprofen (IBU) using molecular dynamics simulations. The area per lipid (APL) was calculated to describe the effect of ibuprofen on the packing properties of the lipid bilayer. The APL was 0.58 nm2 and 0.63 nm2 for the membrane in low and high IBU respectively, and 0.57 nm2 for the membrane without IBU. Our finding showed that the mean square deviation (MSD) increased with increased ibuprofen content. In addition, the order parameter for the hydrocarbon chain of lipids increased with increased ibuprofen content. There was an increment in the transfer free energy after the head group region while it was maximum in the hydrophobic core for hydrogen peroxide (H2O2) (∼6.2 kcal.mol-1) and H2O (∼3.4 kcal.mol-1) which then decreased to respective values of (∼4.6 kcal.mol-1), and (∼2.3 kcal.mol-1) at the center of the bilayer in the presence of IBU. It seems that in the presence of ibuprofen, the free energy profile of the permeability of water and H2O2 significantly decreased. These findings show that ibuprofen significantly influences the physical properties of the bilayer by decreasing the packing and intermolecular interaction in the hydrocarbon chain region and increasing the water permeability of the bilayer. These results may provide insights into the local cytotoxic side effects of ibuprofen and its underlying molecular mechanisms.Communicated by Ramaswamy H. Sarma.

Computational approach based on freely accessible tools for antimicrobial drug design

Antimicrobial drug development is crucial for public health, especially with the emergence of pandemics and drug resistance that prompts the search for new therapeutic resources. In this context, in silico assays consist of a valuable approach in the rational drug design because they enable a faster and more cost-effective identification of drug candidates compared to in vitro screening. However, once a potential drug is identified, in vitro and in vivo assays are essential to verify the expected activity of the compound and advance it through the subsequent stages of drug development. This work aims to outline an in silico protocol that utilizes only freely available computational tools for identifying new potential antimicrobial agents, which is also suitable in the broad spectrum of drug design. Additionally, this paper reviews relevant computational methods in this context and provides a summary of information concerning the protein-ligand interaction.

Membrane-targeted push-pull azobenzenes for the optical modulation of membrane potential

We introduce a family of membrane-targeted azobenzenes (MTs) with a push-pull character as a new tool for cell stimulation. These molecules are water soluble and spontaneously partition in the cell membrane. Upon light irradiation, they isomerize from trans to cis, changing the local charge distribution and thus stimulating the cell response. Specifically, MTs photoisomerization induces clear and reproducible depolarization. The most promising species, MTP2, was extensively studied. Time-resolved spectroscopy techniques provide insights into the excited state evolution and a complete understanding of its isomerization reaction. Molecular Dynamics simulations reveal the spontaneous and stable partitioning of the compound into the cellular membrane, without significant alterations to the bilayer thickness. MTP2 was tested in different cell types, including HEK293T cells, primary neurons, and cardiomyocytes, and a steady depolarization is always recorded. The observed membrane potential modulation in in-vitro models is attributed to the variation in membrane surface charge, resulting from the light-driven modulation of the MT dipole moment within the cell membrane. Additionally, a developed mathematical model successfully captures the temporal evolution of the membrane potential upon photostimulation. Despite being insufficient for triggering action potentials, the rapid light-induced depolarization holds potential applications, particularly in cardiac electrophysiology. Low-intensity optical stimulation with these modulators could influence cardiac electrical activity, demonstrating potential efficacy in destabilizing and terminating cardiac arrhythmias. We anticipate the MTs approach to find applications in neuroscience, biomedicine, and biophotonics, providing a tool for modulating cell physiology without genetic interventions.

Molecular mechanisms of antiproliferative and pro-apoptotic effects of essential oil active constituents in MCF7 and T24 cancer cell lines: in vitro insights and in silico modelling of proapoptotic gene product-compound interactions

This study aims to investigate the in vitro antiproliferative and pro-apoptotic/apoptotic potential of active constituents of essential oils on two cancer cell lines; namely, breast adenocarcinoma (MCF-7) and urinary bladder cancer (T24). Essential oils active constituents (EO-ACs) entail a spectrum of phytochemicals with widely demonstrated anticancer potential. We assessed the effects of eight essential oils active constituents on T24 and MCF-7 cell lines in both dose- (16-1024 µg/mL) and time-dependent manners. Among these, five EO-ACs (citral, carvacrol, eugenol, geraniol, and thymol) exhibited IC50 values, ranging from 24 µg/mL to 34 µg/mL, as determined by the MTT assay over 72 h. It was observed that the mitochondrial membrane potential decreased while ROS generation increased substantially in treated cells compared to the control. The underlying apoptotic pathway with regard to pro-apoptotic/apoptotic genes was explored through qRT-PCR and western blotting, which showed significant (p < 0.05) upregulation of Bax, Bak, caspase 7, caspase 9, and downregulation of Bcl-2, pERK, and pAkt. The in-silico study showed strong interaction of thymol and carvacrol with Caspase 9, with complex binding energies of -6.1 Kcal/mol and - 6.3 Kcal/mol, respectively. In conclusion, EO-ACs, particularly thymol and carvacrol, effectively reduced cell viability, and triggered caspase-dependent apoptosis in both MCF-7 and T-24 cell lines. These findings categorically underscore EO-ACs as promising active compounds for anticancer therapy, warranting further in-depth exploration through in vivo studies.

Dual-specific autophosphorylation of kinase IKK2 enables phosphorylation of substrate IκBα through a phosphoenzyme intermediate

Rapid and high-fidelity phosphorylation of two serines (S32 and S36) of IκBα by a prototype Ser/Thr kinase IKK2 is critical for fruitful canonical NF-κB activation. Here, we report that IKK2 is a dual specificity Ser/Thr kinase that autophosphorylates itself at tyrosine residues in addition to its activation loop serines. Mutation of one such tyrosine, Y169, located in proximity to the active site, to phenylalanine, renders IKK2 inactive for phosphorylation of S32 of IκBα. Surprisingly, auto-phosphorylated IKK2 relayed phosphate group(s) to IκBα without ATP when ADP is present. We also observed that mutation of K44, an ATP-binding lysine conserved in all protein kinases, to methionine renders IKK2 inactive towards specific phosphorylation of S32 or S36 of IκBα, but not non-specific substrates. These observations highlight an unusual evolution of IKK2, in which autophosphorylation of tyrosine(s) in the activation loop and the invariant ATP-binding K44 residue define its signal-responsive substrate specificity ensuring the fidelity of NF-κB activation.

Structural Insights Into the Impact of the Glycine-Rich Loop Mutation in Noonan Syndrome on the ATP Binding Pocket of CRAF Kinase

The pathogenic G361A variant of CRAF, associated with increased intrinsic kinase activity in Noonan syndrome (NS), remains poorly understood in terms of its molecular and structural impact on kinase activity. To elucidate the mechanistic implications of the glycine to alanine substitution at residue 361 in CRAF, we employed molecular dynamics simulations. Our findings reveal that this mutation predominantly affects the ATP binding pocket and critical intermolecular interactions within the active cleft that favors the phosphate transfer reaction. Notably, our data highlight significant alterations in key interactions involving Lys470/Asp486 and ATP.Mg2+ in CRAFG361A that are absent in wild-type CRAF. Additionally, we identified a novel interaction mode between Lys431 and γ-phosphate in wild-type CRAF, a residue evolutionarily conserved in CRAFs but not in related kinases such as BRAF, ARAF, and KSR1/2. Furthermore, observed shifts in the αC-helix and G-loop relative to the wild-type correlate with an enlarged ATP-binding cavity in the mutant, reflecting structural adaptations due to these mutations. Overall, these structural insights underscore the elevated intrinsic kinase activity of the CRAFG361A variant and provide crucial mechanistic details that could inform the development of specific inhibitors targeting this variant.

Molecular dynamics of SARS-CoV-2 omicron variants from Philippine isolates against hesperidin as spike protein inhibitor

SARS-CoV-2 remains a global threat with new sublineages posing challenges, particularly in the Philippines. Hesperidin (HD) is being studied as a potential prophylactic for COVID-19. However, the virus's rapid evolution could alter how HD binds to it, affecting its effectiveness. Here, we study the mutation-induced variabilities of HD dynamics and their effects on molecular energetics in SARS-CoV-2 spike receptor complex systems. We considered eight different point mutations present in the Omicron variant. Root-mean-square deviation and binding energy analysis showed that S477N and Omicron did not eject HD throughout the simulation. Hydrogen bond distribution analysis highlighted the involvement of hydrogen bonding in mutant-HD stabilization, especially for S477N and Omicron. Root-mean-square fluctuation analysis revealed evidence of Y505H destabilization on complex systems, while distal-end loop mutations increased loop flexibility for all models bearing the three mutations. Per-residue energy decomposition demonstrated that Q493R substitution increased HD interaction. Free energy landscape and essential dynamics through principal component analysis provided insights into the conformational subspace distribution of mutant model molecular dynamics trajectories. In conclusion, significant mutations contributed to the HD interaction in different ways. S477N has shown significant binding contributions through favorable ligand interaction, while other mutations contribute via conformational modifications, increased affinity due to sidechain mutations, and increased loop flexibility.

Engineered crystalline polymers for effective contaminant removal from water

Herein, we discuss the structure-function of biomimetic imidazole-quartet substrates (I-quartets) obtained through the adaptive self-assembly of octyl-ureido-polyol structures in polyamide membranes designed as adsorbents. Molecular dynamics (MD) and well-tempered metadynamics simulations are utilized to examine ion contaminants' adsorption process and dynamic behaviors onto alkylureido-ethylimidazoles with well-defined supramolecular structures. Moreover, the atoms-in-molecules (AIM) analysis identified multiple types of atomic interactions between the contaminant molecules and the substrates. The results demonstrate that I-quartets with hydrophobic tails significantly enhance the adsorption of contaminant species in the aquatic environment. Descriptors involving interaction energies mean square displacement, radial distribution function, root-mean-square deviation, the number of hydrogen bonds, and solvent-accessible surface area are estimated from the simulation trajectories to study this process. The system containing PO43- exhibited notable stability, as indicated by data analysis. Electrostatic interactions primarily govern the adsorption process; however, the interaction between the active sites of alkylureido-ethylimidazole-based channels, such as N = C and O = C, and the investigated contaminant species (PO43-, NO3-, NO2-, and HNO3) can enhance adsorption due to these interactions. In addition, the free energy values for the adsorption process of PO43-, NO3-, NO2-, and HNO3 contaminants in water are - 604.77, - 532.63, - 461.24, and - 348.62 kJ mol-1, respectively. The obtained results confirm that alkylureido-ethylimidazoles are prominent adsorbents for removing pollutant ions from wastewater, thus contributing to the development of more efficient materials for water purification.

A modular and extensible CHARMM-compatible model for all-atom simulation of polypeptoids

Peptoids (N-substituted glycines) are a class of sequence-defined synthetic peptidomimetic polymers with applications including drug delivery, catalysis, and biomimicry. Classical molecular simulations have been used to predict and understand the conformational dynamics of single chains and their self-assembly into morphologies including sheets, tubes, spheres, and fibrils. The CGenFF-NTOID model based on the CHARMM General Force Field has demonstrated success in accurate all-atom molecular modeling of peptoid structure and thermodynamics. Extension of this force field to new peptoid side chains has historically required reparameterization of side chain bonded interactions against ab initio data. This fitting protocol improves the accuracy of the force field but is also burdensome and precludes modular extensibility of the model to arbitrary peptoid sequences. In this work, we develop and demonstrate a Modular Side Chain CGenFF-NTOID (MoSiC-CGenFF-NTOID) as an extension of CGenFF-NTOID employing a modular decomposition of the peptoid backbone and side chain parameterizations, wherein arbitrary side chains within the large family of substituted methyl groups (i.e., -CH3, -CH2R, -CHRR', and -CRR'R″) are directly ported from CGenFF. We validate this approach against ab initio calculations and experimental data to develop a MoSiC-CGenFF-NTOID model for all 20 natural amino acid side chains along with 13 commonly used synthetic side chains and present an extensible paradigm to efficiently determine whether a novel side chain can be directly incorporated into the model or whether refitting of the CGenFF parameters is warranted. We make the model freely available to the community along with a tool to perform automated initial structure generation.

Unraveling atomic-scale mechanisms of GDP extraction catalyzed by SOS1 in KRAS-G12 and KRAS-D12 oncogenes

The guanine exchange factor SOS1 plays a pivotal role in the positive feedback regulation of the KRAS signaling pathway. Recently, the regulation of KRAS-SOS1 interactions and KRAS downstream effector proteins has emerged as a key focus in the development of therapies targeting KRAS-driven cancers. However, the detailed dynamic mechanisms underlying SOS1-catalyzed GDP extraction and the impact of KRAS mutations remain largely unexplored. In this study, we unveil and describe in atomic detail the primary mechanisms by which SOS1 facilitates GDP extraction from KRAS oncogenes. For GDP-bound wild-type KRAS (KRAS-G12), four critical amino acids (Lys811, Glu812, Lys939, and Glu942) are identified as essential for the catalytic function of SOS1. Notably, the KRAS-G12D mutation (KRAS-D12) significantly accelerates the rate of GDP extraction. The molecular basis of this enhancement are attributed to hydrogen bonding interactions between the mutant residue Asp12 and a positively charged pocket in the intrinsically disordered region (residues 807-818), comprising Ser807, Trp809, Thr810, and Lys811. These findings provide novel insights into SOS1-KRAS interactions and offer a foundation for developing anti-cancer strategies aimed at disrupting these mechanisms.

G-Protein-Coupled Receptor Surface Creates a Favorable Pathway for Membrane Permeation of Drug Molecules

G-protein-coupled receptors (GPCRs) play a crucial role in modulating physiological responses and serve as the main drug target. Specifically, salmeterol and salbutamol, which are used for the treatment of pulmonary diseases, exert their effects by activating the GPCR β2-adrenergic receptor (β2AR). In our study, we employed coarse-grained molecular dynamics simulations with the Martini 3 force field to investigate the dynamics of drug molecules in membranes in the presence and absence of β2AR. Our simulations reveal that, in more than 50% of the flip-flop events, the drug molecules use the β2AR surface to permeate the membrane. The pathway along the GPCR surface is significantly more energetically favorable for the drug molecules, which was revealed by umbrella sampling simulations along spontaneous flip-flop pathways. Furthermore, we assessed the behavior of drugs with intracellular targets, such as kinase inhibitors, whose therapeutic efficacy could benefit from this observation. In summary, our results show that β2AR surface interactions can significantly enhance the membrane permeation of drugs, emphasizing their potential for consideration in future drug development strategies.

Insertion and Anchoring of the HIV-1 Fusion Peptide into a Complex Membrane Mimicking the Human T-Cell

A fundamental understanding of how the HIV-1 envelope (Env) protein facilitates fusion is still lacking. The HIV-1 fusion peptide, consisting of 15 to 22 residues, is the N-terminus of the gp41 subunit of the Env protein. Further, this peptide, a promising vaccine candidate, initiates viral entry into target cells by inserting and anchoring into human immune cells. The influence of membrane lipid reorganization and the conformational changes of the fusion peptide during the membrane insertion and anchoring processes, which can significantly affect HIV-1 cell entry, remains largely unexplored due to the limitations of experimental measurements. In this work, we investigate the insertion of the fusion peptide into an immune cell membrane mimic through multiscale molecular dynamics simulations. We mimic the native T-cell by constructing a nine-lipid asymmetric membrane, along with geometrical restraints accounting for insertion in the context of gp41. To account for the slow time scale of lipid mixing while enabling conformational changes, we implement a protocol to go back and forth between atomistic and coarse-grained simulations. Our study provides a molecular understanding of the interactions between the HIV-1 fusion peptide and the T-cell membrane, highlighting the importance of the conformational flexibility of fusion peptides and local lipid reorganization in stabilizing the anchoring of gp41 into the targeted host membrane during the early events of HIV-1 cell entry. Importantly, we identify a motif within the fusion peptide critical for fusion that can be further manipulated in future immunological studies.

Molecular Insights into Single-Chain Lipid Modulation of Acid-Sensing Ion Channel 3

Polyunsaturated fatty acids (PUFAs) and their analogs play a significant role in modulating the activity of diverse ion channels, and recent studies show that these lipids potentiate acid-sensing ion channels (ASICs), leading to increased activity. The potentiation of the channel stems from multiple gating changes, but the exact mechanism of these effects remains uncertain. We posit a mechanistic explanation for one of these changes in channel function, the increase in the maximal current, by applying a combination of electrophysiology and all-atom molecular dynamics simulations on open-state hASIC3. Microsecond-scale simulations were performed on open-state hASIC3 in the absence and presence of a PUFA, docosahexaenoic acid (DHA), and a PUFA analogue, N-arachidonyl glycine (AG). Intriguingly, our simulations in the absence of PUFA or PUFA analogs reveal that a tail from the membrane phospholipid POPC inserts itself into the pore of the channel through lateral fenestrations on the sides of the transmembrane segments, obstructing ion permeation through the channel. The binding of either DHA or AG prevented POPC from accessing the pore in our simulations, which relied on the block of ionic conduction by phospholipids. Finally, we use single-channel recording to show that DHA increases the amplitude of the single-channel currents in ASIC3, which is consistent with our hypothesis that PUFAs relieve the pore block of the channel induced by POPCs. Together, these findings offer a potential mechanistic explanation of how PUFAs modulate the ASIC maximal current, revealing a novel mechanism of action for PUFA-induced modulation of ion channels.

Improving the Computational Efficiency of the Adaptive Biasing Force Sampling by Leveraging the Telescopic-Solvation Scheme

The number of solvent molecules present in the system during molecular dynamics is the balancing act between the need to remove the boundary effects present in the system and the computational cost. Application of the telescopic-solvation box scheme during the estimation of the potential of mean force (PMF) can be advantageous in situations where the contribution of solvent far from the site of interest toward the whole PMF is negligible, as previously demonstrated in the case of adaptive steered molecular dynamics and umbrella sampling. This work explores the application of the telescopic-solvation box scheme during enhanced sampling by the stratified adaptive biasing force (ABF) family of methods, including ABF, extended ABF, well-tempered-metadynamics extended ABF, and multiwalker extended ABF. During this scheme, the number of water molecules differed in each stratified window, whose number depended on the value of the collective variable being sampled in that window. Two systems were used to verify the viability of the telescopic scheme: unfolding (Ala)10 peptide in water and insertion of α-tocopherol in a bilayer membrane. In the first system, the 1D and 2D PMFs obtained by the telescopic-solvation scheme matched well with the benchmark PMFs estimated with a standard solvation box. The minimal energy path connecting the α-helical and extended conformational states revealed that the unfolding process of (Ala)10 in water involved multiple closely spaced metastable states. As for the second system, the PMF, equilibrium location of α-tocopherol, and the free energy associated with the desorption and flipping of α-tocopherol obtained within the scope of the telescopic-solvation box scheme agreed with their standard solvation box values. Enhanced sampling with ABF and its variants in conjunction with the telescopic-solvation scheme results in a similar quality of the estimated PMF compared to sampling with a standard solvation box, albeit with reduced computational cost.

Expanding the HP1a-binding consensus and molecular grammar for heterochromatin assembly

The recruitment of Heterochromatin Protein 1 (HP1) partners is essential for heterochromatin assembly and function, yet our knowledge regarding their organization in heterochromatin remains limited. Here we show that interactors engage the Drosophila HP1 (HP1a) dimer through a degenerate and expanded form of the previously identified PxVxL motif, which we now term HP1a Access Codes (HACs). These HACs reside in disordered regions, possess high conservation among Drosophila homologs, and contain alternating hydrophobic residues nested in a cluster of positively charged amino acids. These findings and molecular dynamics simulations identify key electrostatic interactions that modulate HP1a-binding strength and provide a dramatically improved HP1a-binding consensus motif that can reveal protein partners and the molecular grammar involved in heterochromatin assembly. We propose HP1a acts as a scaffold for other heterochromatin components containing HAC motifs, which in turn may regulate the function and higher order structure of the heterochromatin compartment.

Minimalist Natural ORPphilin Macarangin B Delineates OSBP Biological Function

OSBP ligands from the ORPphilin family are chemically complex natural products with promising anticancer properties. Here, we describe macarangin B, a natural racemic flavonoid selective for OSBP, which stands out from other ORPphilins due to its structural simplicity and distinct biological activity. Using a bioinspired strategy, we synthesized both (R,R,R) and (S,S,S)-macarangin B enantiomers, enabling us to study their interaction with OSBP based on their unique optical properties. Experimental and computational analyzes revealed that (R,R,R)-macarangin B has the highest affinity for OSBP. Importantly, both enantiomers showed significantly decreased cytotoxicity compared to other ORPphilins, suggesting OSBP is not the primary target in ORPphilin-induced cell death. Yet, OSBP is an attractive antiviral target, as it is hijacked by many positive-strand RNA viruses. Remarkably, (R,R,R)-macarangin B significantly inhibited Zika virus replication in human cells, highlighting its potential as a lead compound for antiviral drug development.

Deciphering the genetic impact of signal peptide missense CTLA-4 polymorphism with rheumatoid arthritis in the Indian population: A case-control and in silico studies

Cytoplasmic T Lymphocyte Antigen-4 (CTLA-4) gene encodes for a glycoprotein, expressed on activated T-cells to transfer an inhibitory signal to control T-cell activation and proliferation. Techniques coupled with Real-time Polymerase Chain Reaction (PCR) and High-Resolution Melting Analysis (HRMA) were used to screen a missense signal peptide polymorphism (CTLA-4 + 49 A/G rs231775) in the Indian population to detect its association with Rheumatoid Arthritis (RA). Further, the resulting outcome was confirmed by Sanger's sequencing technique, and genotype frequencies were calculated. In eukaryotic cells, the M domain of the Signal Recognition Particle (SRP-54) recognizes the N-terminal region of the Signal Peptide (SP) sequence. SP directs the polypeptide chain into the Sec-61 translocon of the Endoplasmic Reticulum (ER) for further protein modification. As the Single Nucleotide Polymorphism (SNP) rs231775 lies in the signal peptide region of CTLA-4, an in-silico study was also performed to predict the mRNA stability and SP-SRP protein interaction. From the study, it was observed that the genotype frequency of rs231775 SNP G/G homozygous dominant was significantly higher in RA patients than G/A heterozygous dominant and A/A homozygous recessive conditions (Odd Ratio (OR) = 2.0862; 95 % Confidence Interval (C.I) = 1.2584 to 3.4584; Relative Risk (RR) = 1.8507; p = 0.0044). Moreover, the rs231775 SNP G allele frequency was higher in RA than the control group G = 0.407 (40.7 %) vs 0.32 (32 %). In silico approaches of Protein-Protein docking and Molecular Dynamics (MD) simulation reveal CTLA-4 rs231775 SNP (G allele) has destabilized the SP-SRP protein complex, which may affect the translocation of CTLA-4 nascent polypeptide chains into the ER via activating Regulation of Aberrant Protein Production (RAPP) pathway.

Bat RNA viruses employ viral RHIMs orchestrating species-specific cell death programs linked to Z-RNA sensing and ZBP1-RIPK3 signaling

RHIM is a protein motif facilitating the assembly of large signaling complexes triggering regulated cell death. A few DNA viruses employ viral RHIMs mimicking host RHIMs and counteract cell death by interacting with host RHIM-proteins to alleviate antiviral defenses. Whether RNA viruses operate such viral RHIMs remains unknown. Here, we identified viral RHIMs in Nsp13 of SARS-CoV-2 and other bat RNA viruses, providing the basis for bats as the hosts for their evolution. Nsp13 promoted viral RHIM and RNA-binding channel-dependent cell death. However, Nsp13 viral RHIM is more critical for human cell death than in bat-derived Tb1 Lu cells, suggesting species-specific regulation. Nsp13 showed RHIM-dependent interactions with ZBP1 and RIPK3, forming large complexes and promoting ZBP1-RIPK3 signaling-mediated cell death. Intriguingly, the SARS-CoV-2 genome consisted of Z-RNA-forming segments promoting Nsp13-dependent cell death. Our findings reveal the functional viral RHIMs of bat-originated RNA viruses regulating host cell death associated with ZBP1-RIPK3 signaling, indicating possible mechanisms of cellular damage and cytokine storm in bat-originated RNA virus infections.

Unveiling Cathepsin B inhibition with repurposed drugs for anticancer and anti-Alzheimer's drug discovery

Alzheimer's disease (AD) is characterized by the aggregation of amyloid β (Aβ) peptides and the formation of plaques in the brain, primarily derived from the proteolytic degradation of amyloid precursor protein (APP). Cathepsin B (CatB) is a cysteine protease that plays a pivotal role in this process, making it a potential target for the development of anti-Alzheimer's therapies. Apart from AD, CatB is implicated in various physiological and pathological processes, including cancer. Given the critical role of CatB in these diseases, identifying effective inhibitors is of significant therapeutic interest. In this study, we employed a systematic virtual screening approach using repurposed molecules from the DrugBank database to identify potential CatB inhibitors. Primarily, we focused on binding affinities and selectivity to pinpoint potential hits against CatB. Two repurposed molecules, Lurasidone and Paliperidone, emerged as promising candidates with significant affinity for CatB. These molecules demonstrated favorable drug profiles and exhibited preferential binding to the catalytic pocket of CatB via interacting with functionally significant residues. To further explore the binding mechanism and stability of the CatB-drug complexes, molecular dynamics (MD) simulations were conducted for 500 ns. The results revealed that CatB and Lurasidone, as well as Paliperidone, form stable complexes throughout the simulation. Taken together, the findings suggest that Lurasidone and Paliperidone can act as repurposed CatB inhibitors with potential applications in the development of therapeutics against AD and other CatB-associated diseases after further validation.

Investigating the Bromoform Membrane Interactions Using Atomistic Simulations and Machine Learning: Implications for Climate Change Mitigation

Methane emissions from livestock contribute to global warming. Seaweeds used as food additive offer a promising emission mitigation strategy because seaweeds are enriched in bromoform─a methanogenesis inhibitor. Therefore, understanding bromoform storage and production in seaweeds and particularly in a cell-like environment is crucial. As a first step toward this aim, we present an atomistic description of bromoform dynamics, diffusion, and aggregation in the presence of lipid membranes. Using all-atom molecular dynamics simulations with customized CHARMM-formatted bromoform force field files, we investigate the interactions of bromoform and lipid bilayer across various concentrations. Bromoform penetrates membranes and at high concentrations forms aggregates outside the membrane without affecting membrane thickness or lipid tail order. Aggregates outside the membrane influence the membrane curvature. Within the membrane, bromoform preferentially localizes in the membrane hydrophobic core and diffuses the slowest along the membrane normal. Employing general local-atomic descriptors and unsupervised machine learning, we demonstrate the similarity of bromoform local structures between the liquid and aggregated forms.

Quest for discovering novel CDK12 inhibitor

CDK12 is essential for cellular processes like RNA processing, transcription, and cell cycle regulation, inhibiting cancer cell growth and facilitating macrophage invasion. CDK12 is a significant oncogenic factor in various cancers, including HER2-positive breast cancer, Anaplastic thyroid carcinoma, Hepatocellular carcinoma, prostate cancer, and Ewing sarcoma. It is also regarded as a potential biomarker, emphasizing its broader significance in oncology. Targeting CDK12 offers a promising strategy to develop therapy. Various monoclonal antibodies have drawn wide attention, but they are expensive compared to small-molecule inhibitors, limiting their accessibility and affordability for patients. Consequently, this research aims to identify effective CDK12 inhibitors using comprehensive high-throughput virtual screening. RASPD protocol has been employed to screen three different databases against the target followed by drug-likeness, molecular docking, ADME, toxicity, Consensus molecular docking, MD Simulation, and in-vitro studies MTT assay. The research conducted yielded one compound ZINC11784547 has demonstrated robust binding affinity, favorable ADME features, less toxicity, remarkable stability, and cytotoxic effect. The identified compound holds promise for promoting cancer cell death through CDK12 inhibition.

Sequence of the SARS-CoV-2 Spike Transmembrane Domain Encodes Conformational Dynamics

The homotrimeric SARS-CoV-2 spike protein enables viral infection by undergoing a large conformational transition, which facilitates the fusion of the viral envelope with the host cell membrane. The spike protein is anchored to the SARS-CoV-2 envelope by its transmembrane domain (TMD), composed of three TM helices, each contributed by one of the protomers of spike. Although the TMD is known to be important for viral fusion, whether it is a passive anchor of the spike or actively promotes fusion remains unknown. Specifically, it is unclear if the TMD and its dynamics facilitate the prefusion to postfusion conformational transition of the spike. Here, we computationally study the dynamics and self-assembly of the SARS-CoV-2 spike TMD in homogeneous POPC and cholesterol containing membranes. Atomistic simulations of a long TM helix-containing protomer segment show that the membrane-embedded segment bobs, tilts and gains and loses helicity, locally thinning the membrane. Coarse-grained multimerization simulations using representative TM helix structures from the atomistic simulations exhibit diverse trimer populations whose architecture depends on the structure of the TM helix protomer. While a symmetric conformation reflects the symmetry of the resting spike, an asymmetric TMD conformation could promote membrane fusion through the stabilization of a fusion intermediate. Together, our simulations demonstrate that the sequence and length of the SARS-CoV-2 spike TM segment make it inherently dynamic, that trimerization does not abrogate these dynamics and that the various observed TMD conformations may enable viral fusion.

Terminal Tryptophan-Directed Anisotropic Self-Assembly for Precise Protein Nanostructure Regulation

A common challenge in nanotechnology is synthesizing nanomaterials with well-defined structures. In particular, it remains a major unresolved challenge to precisely regulate the structure and function of protein nanomaterials, which are structurally diverse, highly ordered, and complex and offer an innovative means that enables a high performance in various nanodevices, which is rarely achievable with other nanomaterials. Here an innovative approach is proposed to fabricating multi-dimensional (0- to 3D) protein nanostructures with functional and structural specialties via molecular-level regulation. This approach is based on a stable, consistent, anisotropic self-assembly of Tobacco mosaic virus (TMV) coat protein-derived engineered building blocks where genetically added tryptophan residues are externally tailored. The unique structural characteristics of each nanostructure above are demonstrated in detail through various analyses (electron microscopy, atomic force microscopy, dynamic light scattering, and small-angle X-ray scattering) and further investigated through molecular dynamics simulations, indicating that this control, anisotropic, and molecular assembly-based approach to regulating protein nanostructures holds great potential for customizing a variety of nanomaterials with unique functions and structures.

Molecular Dynamics Simulations of Structurally Nanoengineered Antimicrobial Peptide Polymers Interacting with Bacterial Cell Membranes

Multidrug resistance (MDR) to conventional antibiotics is one of the most urgent global health threats, necessitating the development of effective and biocompatible antimicrobial agents that are less inclined to provoke resistance. Structurally nanoengineered antimicrobial peptide polymers (SNAPPs) are a novel and promising class of such alternatives. These star-shaped polymers are made of a dendritic core with multiple arms made of copeptides with varying amino acid sequences. Through a comprehensive set of in vivo experiments, we previously showed that SNAPPs with arms made of random blocks of lysine (K) and valine (V) residues exhibit sub-μM efficacy against Gram-negative and Gram-positive bacteria tested. Cryo-TEM images suggested pore formation by a SNAPP with random block copeptide arms as one of their modes of actions. However, the molecular mechanisms responsible for this mode of action of SNAPPs are not fully understood. To address this gap, we employed an atomistic molecular dynamics simulation technique to investigate the influence of three different sequences of amino acids, namely (1) alt-block KKV, (2) ran-block, and (3) diblock motifs on the secondary structure of their arms and SNAPP's overall configuration as well as their interactions with lipid bilayer. We, for the first time, identified a step-by-step mechanism through which alt-block and random SNAPPs interact with lipid bilayer and lead to "pore formation", hence, cell death. These insights provide a strong foundation for further optimization of the chemical structure of SNAPPs for maximum performance against MDR bacteria, therefore offering a promising avenue for addressing antibiotic resistance and the development of effective antibacterial agents.

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

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

Structure-based virtual screening of Trachyspermum ammi metabolites targeting acetylcholinesterase for Alzheimer's disease treatment

In recent decades, Alzheimer's disease (AD) has garnered significant attention due to its rapid global prevalence. The cholinergic hypothesis posits that the degradation of acetylcholine by acetylcholinesterase (AChE) contributes to AD development. Despite existing anti-AChE drugs, their adverse side effects necessitate new agents. This study analyzed 150 bioactive phytochemicals from Trachyspermum ammi using structure-based drug design and various in-silico tools to identify potent anti-AChE compounds. Compounds were screened for drug-likeness (QEDw ≥50%) and bioavailability (≥55%) and underwent toxicity profiling via the ProTox-II server. Selected compounds were prepared for molecular docking with the human AChE protein as the receptor. Viridifloral, 2-Methyl-3-glucosyloxy-5-isopropyl phenol, Alpha-Curcumene, and Sterol emerged as top candidates with high AChE affinity. These results were validated by molecular dynamics simulations, confirming stable interactions. The hit compounds were further evaluated for drug-likeness using Lipinski's rule and ADMET properties, confirming favorable pharmacokinetic profiles. DFT optimization analyzed frontier molecular orbitals and electrostatic potential, demonstrating favorable chemical reactivity and stability. This study suggests that these identified compounds could be novel nature-derived AChE inhibitors, potentially contributing to AD treatment. However, further in-vitro and in-vivo studies are necessary to confirm their efficacy in biological systems. Future research will focus on developing these compounds into safe and effective drugs to combat Alzheimer's disease.

Structural and functional insights into recombinant β-glucosidase from Thermothelomyces thermophilus: Cello-oligosaccharide hydrolysis and thermostability

β-glucosidases (BGLs) are key enzymes in the depolymerization of cellulosic biomass, catalyzing the conversion of cello-oligosaccharides into glucose. This conversion is pivotal for enhancing the production of second-generation ethanol or other value-added products in biorefineries. However, the process is often cost-prohibitive due to the high enzyme loadings required. Therefore, the discovery of new highly efficient BGLs represents a significant advancement. In this study, a BGL from the glycoside hydrolase family 3 (GH3) of the thermophilic fungus Thermothelomyces thermophilus (TthBgl3A) was heterologously expressed in Aspergillus nidulans. The recombinant enzyme exhibited optimal activity at pH 5.0 and 55 °C, with noteworthy stability for up to 160 h. A distinctive, extensive loop within the catalytic cavity of TthBgl3A facilitates hydrophobic interactions that enhance the binding and hydrolysis of long cello-oligosaccharides. Consequently, TthBgl3A has proven to be an efficient enzyme for the hydrolysis lignocellulosic biomass. These findings are significant for expanding the repertoire of enzymes produced by T. thermophilus and provide new insights into the potential application of TthBgl3A in the degradation of cellulosic materials and the production of valuable compounds.

Employing spectroscopic, calorimetric and structural bioinformatics approaches to decipher the binding mechanism of mangiferin with human transferrin

In recent times, neurodegenerative diseases (NDs), such as Alzheimer's disease (AD), Parkinson's disease (PD) and others, represent a major global health challenge with increasing prevalence and significant socio-economic impact. These diseases, characterized by progressive neuronal loss, currently lack effective therapies. Phytochemicals offer promising therapeutic potential due to their diverse bioactive properties. Mangiferin, a glucosylxanthone found in mangoes and other plants, has shown significant therapeutic potential in NDs. Human transferrin (Tf), an iron-binding protein crucial for iron homeostasis, is implicated in ND pathogenesis. This study delineates the interaction between Mangiferin and Tf. Molecular docking revealed Mangiferin predominantly interacts with Tf's binding site, engaging critical residues. Molecular dynamics simulations over 200 ns demonstrated the stability of the Tf-Mangiferin complex without major deviations. Fluorescence binding assays confirmed the strong binding affinity of Mangiferin to Tf. Additionally, Isothermal titration calorimetry (ITC) validated the spontaneous binding of Mangiferin with Tf, providing detailed thermodynamic parameters. The findings highlight the therapeutic potential of Mangiferin in NDs treatment through its interaction with Tf, offering insights into novel mechanisms of action and pathways for disease modification.

Aged Garlic Extract (AGE) and Its Constituent S-Allyl-Cysteine (SAC) Inhibit the Expression of Pro-Inflammatory Genes Induced in Bronchial Epithelial IB3-1 Cells by Exposure to the SARS-CoV-2 Spike Protein and the BNT162b2 Vaccine

Garlic (Allium sativum L.) is a species of the onion family (Alliaceae ) widely used as a food and a folk medicine. The objective of this study was to determine the effects of AGE (aged garlic extract) on pro-inflammatory genes relevant to COVID-19. To this aim, we treated bronchial epithelial IB3-1 cells with SARS-CoV-2 spike protein (S-protein) or with the COVID-19 BNT162b2 vaccine in the absence or in the presence of AGE. The results obtained demonstrated that AGE is a potent inhibitor of the S-protein-induced expression of the IL-1β, IL-6 and IL-8 genes. Bio-Plex analysis demonstrated that AGE reduced release of IL-6 and IL-8, which were highly induced by S-protein. No inhibition of cells’ growth, toxicity and pro-apoptotic effects were found in AGE-treated cells. The effects of one of the major AGE constituents (S-allyl cysteine, SAC) were studied on the same experimental model systems. SAC was able to inhibit the S-protein-induced expression of IL-1β, IL-6 and IL-8 genes and extracellular release of IL-6 and IL-8, confirming that S-allyl-cysteine is one of the constituents of AGE that is responsible for inhibiting S-protein-induced pro-inflammatory genes. Docking experiments suggest that a possible mechanism of action of SAC is an interference with the activity of Toll-like receptors (TLRs), particularly TLR4, thereby inhibiting NF-κB- and NF-κB-regulated genes, such as IL-1β, IL-6 and IL-8 genes. These results suggest that both AGE and SAC deserve further experimental efforts to verify their effects on pro-inflammatory genes in SARS-CoV-2-infected cells.

Investigating the impact of SOD1 mutations on amyotrophic lateral sclerosis progression and potential drug repurposing through in silico analysis

Superoxide dismutase 1 (SOD1) is a vital enzyme responsible for attenuating oxidative stress through its ability to facilitate the dismutation of the superoxide radical into oxygen and hydrogen peroxide. The progressive loss of motor neurons characterize amyotrophic lateral sclerosis (ALS), a crippling neurodegenerative disease that is caused by mutations in the SOD1 gene. In this study, in silico mutational analysis was performed to study the various mutations, the pathogenicity and stability ΔΔG (binding free energy) of the variant of SOD1. x in the protein variant analysis showed a considerable destabilizing effect with a ΔΔG value of -4.2 kcal/mol, signifying a notable impact on protein stability. Molecular dynamics simulations were conducted on both wild-type and C146R mutant SOD1. RMSD profiles indicated that both maintained consistent structural conformation over time. Additionally, virtual screening of 3067 FDA-approved drugs against the mutant SOD1 identified two potential binders, Tucatinib (51039094) and Regorafenib (11167602), which interacted with Leu106, similar to the control drug, Ebselen. Further simulations assessed the dynamic properties of SOD1 in monomeric and dimeric forms while bound to these compounds. 11167602 maintained stable interaction with the monomeric SOD1 mutant, whereas 51039094 and Ebselen dissociated from the monomeric protein's binding site. However, all three compounds were stably bound to the dimeric SOD1. MM/GBSA analysis revealed similar negative binding free energies for 11167602 and 51039094, identifying them as strong binders due to their interaction with Cys111. Experimental validation, including in vitro, cell-based, and in vivo assays are essential to confirm these candidates before advancing to clinical trials.

Balancing Group 1 Monoatomic Ion-Polar Compound Interactions in the Polarizable Drude Force Field: Application in Protein and Nucleic Acid Systems

An accurate force field (FF) is the foundation of reliable results from molecular dynamics (MD) simulations. In our recently published work, we developed a protocol to generate atom pair-specific Lennard-Jones (known as NBFIX in CHARMM) and through-space Thole dipole screening (NBTHOLE) parameters in the context of the Drude polarizable FF based on readily accessible quantum mechanical (QM) data to fit condensed phase experimental thermodynamic benchmarks, including the osmotic pressure, diffusion coefficient, ionic conductivity, and solvation free energy, when available. In the present work, the developed protocol is applied to generate NBFIX and NBTHOLE parameters for interactions between monatomic ions (specifically Li+, Na+, K+, Rb+, Cs+, and Cl-) and common functional groups found in proteins and nucleic acids. The parameters generated for each ion-functional group pair were then applied to the corresponding functional groups within proteins or nucleic acids followed by MD simulations to analyze the distribution of ions around these biomolecules. The modified FF successfully addresses the issue of overbinding observed in a previous iteration of the Drude FF. Quantitatively, the model accurately reproduces the effective charge of proteins and demonstrates a level of charge neutralization for a double-helix B-DNA in good agreement with the counterion condensation theory. Additionally, simulations involving ion competition correlate well with experimental results, following the trend Li+ > Na+ ≈ K+ > Rb+. These results validate the refined model for group 1 ion-biomolecule interactions that will facilitate the application of the polarizable Drude FF in systems in which group 1 ions play an important role.

Potent and Selective Human 5-HT2B Serotonin Receptor Antagonists: 4'-Cyano-(N)-methanocarba-adenosines by Synthetic Serendipity

Rigidified nucleoside derivatives with (N)-methanocarba replacement of ribose have been repurposed as peripheral subtype-selective 5-HT2B serotonin receptor antagonists for heart and lung fibrosis and intestinal/vascular conditions. 4'-Cyano derivative 40 (MRS8209; Ki, 4.27 nM) was 47-fold (human binding, but not rat and mouse) and 724-fold (functionally) selective at 5-HT2BR, compared to antitarget 5-HT2CR, and predicted to form a stable receptor complex using docking and molecular dynamics. 4'-Cyano substituents enhanced 5-HT2BR affinity (typically 4-5-fold compared to 4'-CH2OH), depending on an N6 group larger than methyl. Asymmetric N6 groups (4'-cyano-2-halo derivatives 33-35 and 37) provided potent 5-HT2BR Ki values (7-22 nM). A 4'-CH2CN substituent was less effective than 4'-CN at increasing 5-HT2BR affinity, while a 4'-CHF2 group produced high 5-HT2B affinity/selectivity. A 2-benzylthio-adenine group with unsubstituted 6-NH2 shifted the typical selectivity pattern toward potent 5-HT2C binding. Thus, the SAR suggests that N6-cyclopentyl-4'-cyano modifications are promising, with an interdependence among the substituent positions.

Conformational response of αIIbβ3 and αVβ3 integrins to force

As major adhesion receptors, integrins transmit biochemical and mechanical signals across the plasma membrane. These functions are regulated by transitions between bent and extended conformations and modulated by force. To understand how force on integrins mediates cellular mechanosensing, we compared two highly homologous integrins, αIIbβ3 and αVβ3. These integrins, expressed in circulating platelets vs. solid tissues, respectively, share the β3 subunit, bind similar ligands and have similar bent and extended conformations. Here, we report that in cells expressing equivalent levels of each integrin, αIIbβ3 mediates spreading on softer substrates than αVβ3. These effects correlate with differences in structural dynamics of the two integrins under force. All-atom simulations show that αIIbβ3 is more flexible than αVβ3 due to correlated residue motions within the α subunit domains. Single molecule measurements confirm that αIIbβ3 extends faster than αVβ3. These results reveal a fundamental relationship between protein function and structural dynamics in cell mechanosensing.

Effects of Nicotine on the Thermodynamics and Phase Coexistence of Pulmonary Surfactant Model Membranes

Phase separation is essential for membrane function, and alterations in phase coexistence by membrane-interacting molecules, such as nicotine, can impair membrane stability. With the increasing use of e-cigarettes, concerns have arisen about the impact of nicotine on pulmonary surfactants. Here, we used differential scanning calorimetry (DSC), molecular dynamics (MD) simulations, and electron spin resonance (ESR) to examine nicotine's effect on the phase coexistence of two surfactant models: pure DPPC and a DPPC/POPC/POPG mixture. Our DSC analysis revealed that nicotine interacts with both membranes, increasing enthalpy and entropy change during the phase transition. ESR revealed that nicotine affects membrane fluidity and packing of DPPC more effectively than the ternary mixture, especially near the surface. MD simulations showed that neutral nicotine resides in the mid-plane, while protonated nicotine remains near the surface. Nicotine binding to the membranes is dynamic, switching between bound and unbound states. Analysis via ESR/van't Hoff method revealed changes in the thermodynamics of phase coexistence, yielding distinct non-linear behavior. Nicotine altered the temperature dependence of the free energy, modifying the thermodynamic driving forces and the balance of non-covalent lipid interactions. These findings provide new insights into how nicotine influences pulmonary surfactant model membranes, with potential implications for surfactant function.

Dynamic interplay between a TonB-dependent heme transporter and a TonB protein in a membrane environment

The envelope of Gram-negative bacteria is composed of two membranes separated by the periplasmic space. This organization imposes geometrical and distance constraints that are key for the mechanism of action of multicomponent systems spanning the envelope. However, consideration of all three compartments by experimental approaches is still elusive. Here, we have used the state-of-the-art molecular dynamics simulation in an Escherichia coli envelope model to obtain a dynamic view of molecular interactions between the outer membrane heme transporter HasR and the inner membrane TonB-like protein HasB. Their interaction allows the transfer of the inner membrane proton-motive force derived energy to the transporter for heme internalization. The simulations that incorporate both membranes show the key role of periplasmic domains of both proteins and their dynamics in complex formation and stability. They revealed a previously unidentified network of HasR-HasB protein-protein interactions in the periplasm. Experimental validation (mutations, in vivo phenotypic and biophysical assays) provides support for the simulation-predicted interactions. Based on structural and sequence conservation, the network of interaction revealed in this study is expected to occur in other nutrient import systems.

IMPORTANCE

Gram-negative bacteria import scarce nutrients such as metals and vitamins by an energized mechanism involving a multicomponent protein system that spans the cell envelope. It consists of an outer membrane TonB-dependent transporter (TBDT) and a TonB complex in the inner membrane that provides the proton motive force energy for the nutrient entry. Despite the intense research efforts focused on this system (a) from structural and fundamental microbiology perspectives and (b) for the interest in the development of new antibacterial strategies, the molecular mechanism of the system is not at all well understood. The lack of understanding comes from incomplete structural data and the experimental difficulties of studying an inherently flexible multicomponent complex that resides within the heterogeneous environment of the double membrane bacterial cell envelope. To address these challenges and obtain a comprehensive view of the molecular interactions at atomic level, here, we have used the combined power of advanced molecular simulations and complementary microbiology and biochemical experiments. Our results represent a significant step forward in understanding the structural and molecular bases of this vital mechanism.

Unraveling the molecular mechanisms of ALS: a network biology and structural modeling approach of investigating the impact of C9orf72 mutations

C9orf72 is a major genetic factor in Amyotrophic Lateral Sclerosis (ALS), a neurodegenerative disorder affecting brain and spinal cord neurons, and comprehending its mutational impact is crucial for developing ALS therapies. Therefore, the current study's protein-protein interaction (PPI) network for C9orf72 was meticulously mapped to identify key interactors that might influence the disease mechanism. Among the identified proteins, SMCR8 emerged as a prominent candidate due to its high connectivity (total network contribution = 7.896) within the C9orf72-associated network, suggesting a potential role in modulating the effects of C9orf72 mutations. Analysis of C9orf72 mutations highlighted the I525T mutation, which significantly destabilizes the protein, as indicated by a ΔΔG value of -2.02 kcal/mol. Further investigation involved comparing the structural dynamics of the wild-type C9orf72 and its mutant variants through molecular docking and dynamics simulations. The wild-type demonstrated more stable structural conformation over time, as shown by its RMSD profile than its mutant counterpart. However, after 80 nanoseconds, the mutant variant achieved a similar RMSD stability level. Intriguingly, the mutant formed a more stable complex with SMCR8, evident from its lower binding free energy (-64.18 kcal/mol compared to the wild type's -34.82 kcal/mol). Moreover, per-residue decomposition analysis further revealed critical interactions at specific residues. The wild-type protein showed a significant stabilizing interaction at Arg785, whereas the mutant favored Arg262, indicating a potential shift in binding affinity and site due to the mutation. This shift suggests an altered binding landscape in the mutant C9orf72, which might contribute to the dysregulated protein interactions and cellular processes associated with ALS pathology. The study thus underscores the pathological hyper-stability of the mutant C9orf72, highlighting its potential role in the progression of ALS.

Data Quality in the Fitting of Approximate Models: A Computational Chemistry Perspective

Empirical parametrization underpins many scientific methodologies including certain quantum-chemistry protocols [e.g., density functional theory (DFT), machine-learning (ML) models]. In some cases, the fitting requires a large amount of data, necessitating the use of data obtained using low-cost, and thus low-quality, means. Here we examine the effect of using low-quality data on the resulting method in the context of DFT methods. We use multiple G2/97 data sets of different qualities to fit the DFT-type methods. Encouragingly, this fitting can tolerate a relatively large proportion of low-quality fitting data, which may be attributed to the physical foundations of the DFT models and the use of a modest number of parameters. Further examination using "ML-quality" data shows that adding a large amount of low-quality data to a small number of high-quality ones may not offer tangible benefits. On the other hand, when the high-quality data is limited in scope, diversification by a modest amount of low-quality data improves the performance. Quantitatively, for parametrizing DFT (and perhaps also quantum-chemistry ML models), caution should be taken when more than 50% of the fitting set contains questionable data, and that the average error of the full set is more than 20 kJ mol-1. One may also follow the recently proposed transferability principles to ensure diversity in the fitting set.

Influence of branched ligand architectures on nanoparticle interactions with lipid bilayers

Gold nanoparticles functionalized with organic cationic ligands have shown promise as biomedical agents, but their interactions with cellular membranes are not yet well-understood and design rules for ligands that promote desired cellular interactions are lacking. Past experimental studies have demonstrated that ligand lipophilicity, quantified by the ligand end group partition coefficient, can be used as a descriptor for predicting nano-bio interactions, but such a descriptor is incapable accounting for ligand architecture, such as chain branching. To probe the effects of ligand end group architecture on ligand-lipid interactions, we perform molecular dynamics simulations to investigate how ligand alkyl chain branching modulates the thermodynamics and mechanisms of nanoparticle adsorption to lipid membranes. We designed four pairs of 2 nm diameter gold nanoparticles where each pair had ligand end groups with similar lipophilicity but varying alkyl chain architecture (e.g., one long alkyl chain vs. two short chains) to isolate branching effects from lipophilicity. Free energy calculations and mechanistic insight revealed that alkyl end group branching can decrease free energy barriers for adsorption by disrupting ligand monolayer packing, increasing end group protrusions that lead to favorable ligand intercalation with minimal membrane disruption. Furthermore, increased end group branching promotes adsorption by increasing the exposure of nonpolar surface area to water, which results in a greater reduction of free energy upon exposure to the nonpolar core of the lipid bilayer. These results show that ligand chain architecture can modulate nano-bio interactions, limiting the exclusive use of lipophilicity as a descriptor to predict cellular uptake of surface-functionalized nanoparticles.

Molecular insights into the activation mechanism of GPR156 in maintaining auditory function

The class C orphan G-protein-coupled receptor (GPCR) GPR156, which lacks the large extracellular region, plays a pivotal role in auditory function through Gi2/3. Here, we firstly demonstrate that GPR156 with high constitutive activity is essential for maintaining auditory function, and further reveal the structural basis of the sustained role of GPR156. We present the cryo-EM structures of human apo GPR156 and the GPR156-Gi3 complex, unveiling a small extracellular region formed by extracellular loop 2 (ECL2) and the N-terminus. The GPR156 dimer in both apo state and Gi3 protein-coupled state adopt a transmembrane (TM)5/6-TM5/6 interface, indicating the high constitutive activity of GPR156 in the apo state. Furthermore, C-terminus in G-bound subunit of GPR156 plays a dual role in promoting G protein binding within G-bound subunit while preventing the G-free subunit from binding to additional G protein. Together, these results explain how GPR156 constitutive activity is maintained through dimerization and provide a mechanistic insight into the sustained role of GPR156 in maintaining auditory function.

Multi-omics and in-silico approach reveals AURKA, AURKB, and RSAD2 as therapeutic biomarkers in OSCC progression

Oral squamous cell carcinoma (OSCC), a prevalent form of head and neck cancer, poses a significant health challenge with limited improvements in patient outcomes over the years. Its development is influenced by a complex interplay of genetic alterations and environmental factors. While progress has been made in understanding the molecular mechanisms driving OSCC, pinpointing critical molecular markers and potential drug candidates has proven elusive. This study uniquely endeavors to conduct a meta-analysis to unveil therapeutic genes responsible for OSCC tumorigenesis. A multi-omics approach identified 951 differentially expressed genes (DEGs) associated with OSCC by analyzing microarray data from the NCBI GEO database. Weighted gene co-expression network analysis (WGCNA) detected a significant hub gene module comprising 805 genes, followed by the construction of protein-protein interaction network resulting in two small clusters of 7 gene-encoded proteins each. These clusters were filtered out based on top 10 significant pathways and gene ontology terms to identify six key target proteins with elevated expression levels, acting as potential therapeutic biomarkers for OSCC. Notably, RSAD2 emerged as a novel biomarker linked to OSCC progression. Furthermore, we identified potential inhibitors targeting AURKA, AURKB, and RSAD2 proteins and validated their interactions through molecular dynamics simulation studies. The simulations confirmed the stability of receptor-ligand complexes, suggesting ZINC03839281, ZINC04026167, and ZINC00718292 compounds hold promise as potential inhibitors for therapeutically targeting AURKA, AURKB, and RSAD2 as significant OSCC biomarkers. We recommend further comprehensive studies, including experimental and preclinical investigations, to validate the effectiveness of these lead compounds for OSCC treatment.