Methods of protein structure comparison

Molecular insights on Eltrombopag: potential mitogen stimulants, angiogenesis, and therapeutic radioprotectant through TPO-R activation

The purpose of this study is to investigate the molecular interactions and potential therapeutic uses of Eltrombopag (EPAG), a small molecule that activates the cMPL receptor. EPAG has been found to be effective in increasing platelet levels and alleviating thrombocytopenia. We utilized computational techniques to predict and confirm the complex formed by the ligand (EPAG) and the Thrombopoietin receptor (TPO-R) cMPL, elucidating the role of RAS, JAK-2, STAT-3, and other essential elements for downstream signaling. Molecular dynamics (MD) simulations were employed to evaluate the stability of the ligand across specific proteins, showing favorable characteristics. For the first time, we examined the presence of TPO-R in human umbilical cord mesenchymal stem cells (hUCMSC) and human gingival mesenchymal stem cells (hGMSC) proliferation. Furthermore, treatment with EPAG demonstrated angiogenesis and vasculature formation of endothelial lineage derived from both MSCs. It also indicated the activation of critical factors such as RUNX-1, GFI-1b, VEGF-A, MYB, GOF-1, and FLI-1. Additional experiments confirmed that EPAG could be an ideal molecule for protecting against UVB radiation damage, as gene expression (JAK-2, ERK-2, MCL-1, NFkB, and STAT-3) and protein CD90/cMPL analysis showed TPO-R activation in both hUCMSC and hGMSC. Overall, EPAG exhibits significant potential in treating radiation damage and mitigating the side effects of radiotherapy, warranting further clinical exploration.

In silico and in vivo analysis reveal impact of c-Myc tag in FMC63 scFv-CD19 protein interface and CAR-T cell efficacy

Anti-CD19 CAR-T cell therapy represents a breakthrough in the treatment of B-cell malignancies, and it is expected that this therapy modality will soon cover a range of solid tumors as well. Therefore, a universal cheap and sensitive method to detect CAR expression is of foremost importance. One possibility is the use of epitope tags such as c-Myc, HA or FLAG tags attached to the CAR extracellular domain, however, it is important to determine whether these tags can influence binding of the CAR with its target molecule. Here, we conducted in-silico structural modelling of an FMC63-based anti-CD19 single-chain variable fragment (scFv) with and without a c-Myc peptide tag added to the N-terminus portion and performed molecular dynamics simulation of the scFv with the CD19 target. We show that the c-Myc tag presence in the N-terminus portion does not affect the scFv's structural equilibrium and grants more stability to the scFv. However, intermolecular interaction potential (IIP) analysis reveals that the tag can approximate the complementarity-determining regions (CDRs) present in the scFv and cause steric impediment, potentially disturbing interaction with the CD19 protein. We then tested this possibility with CAR-T cells generated from human donors in a Nalm-6 leukemia model, showing that CAR-T cells with the c-Myc tag have overall worse antitumor activity, which was also observed when the tag was added to the C-terminus position. Ultimately, our results suggest that tag addition is an important aspect of CAR design and can influence CAR-T cell function, therefore its use should be carefully considered.

Development of a novel representation of drug 3D structures and enhancement of the TSR-based method for probing drug and target interactions

Understanding the mechanisms underlying interactions between drugs and target proteins is critical for drug discovery. In our earlier studies, we introduced the Triangular Spatial Relationship (TSR)-based algorithm, which enables the representation of a protein's 3D structure as a vector of integers (TSR keys). These TSR keys correspond to substructures of the 3D structure of a protein and are computed based on the triangles constructed by all possible triples of Cα atoms within the protein. In this study, we report on a new TSR-based algorithm for probing drug and target interactions. Specifically, we have extended the previous algorithm in three novel directions: TSR keys for representing the 3D structure of a drug or a ligand, cross TSR keys between drugs and their targets and intra-residual TSR keys for phosphorylated amino acids. The outcomes illustrate the key contributions as follows: (i) The TSR-based method, which uses the TSR keys as features, is unique in its capability to interpret hierarchical relationships of drugs as well as drug - target complexes using common and specific TSR keys. (ii) The method can distinguish not only the binding sites from the rest of the protein structures, but also the binding sites of primary targets from those of off-targets. (iii) The method has the potential to correlate the 3D structures of drugs with their functions. (iv) Representation of 3D structures by TSR keys has its unique advantage in terms of ease of making searching for similar substructures across structure datasets easier. In summary, this study presents a novel computational methodology, with significant advantages, for providing insights into the mechanism underlying drug and target interactions.

Network pharmacology, molecular docking, and dynamics analyses to predict the antiviral activity of ginger constituents against coronavirus infection

COVID-19 is a global pandemic that caused a dramatic loss of human life worldwide, leading to accelerated research for antiviral drug discovery. Herbal medicine is one of the most commonly used alternative medicine for the prevention and treatment of many conditions including respiratory system diseases. In this study, a computational pipeline was employed, including network pharmacology, molecular docking simulations, and molecular dynamics simulations, to analyze the common phytochemicals of ginger rhizomes and identify candidate constituents as viral inhibitors. Furthermore, experimental assays were performed to analyze the volatile and non-volatile compounds of ginger and to assess the antiviral activity of ginger oil and hydroalcoholic extract. Network pharmacology analysis showed that ginger compounds target human genes that are involved in related cellular processes to the viral infection. Docking analysis highlighted five pungent compounds and zingiberenol as potential inhibitors for the main protease (Mpro), spike receptor-binding domain (RBD), and human angiotensin-converting enzyme 2 (ACE2). Then, (6)-gingerdiacetate was selected for molecular dynamics (MD) simulations as it exhibited the best binding interactions and free energies over the three target proteins. Trajectories analysis of the three complexes showed that RBD and ACE2 complexes with the ligand preserved similar patterns of root mean square deviation (RMSD) and radius of gyration (Rg) values to their respective native structures. Finally, experimental validation of the ginger hydroalcoholic extract confirmed the existence of (6)-gingerdiacetate and revealed the strong antiviral activity of the hydroalcoholic extract with IC50 of 2.727 μ g / ml . Our study provides insights into the potential antiviral activity of (6)-gingerdiacetate that may enhance the host immune response and block RBD binding to ACE2, thereby, inhibiting SARS-CoV-2 infection.

Unlocking the power of AI models: exploring protein folding prediction through comparative analysis

Protein structure determination has made progress with the aid of deep learning models, enabling the prediction of protein folding from protein sequences. However, obtaining accurate predictions becomes essential in certain cases where the protein structure remains undescribed. This is particularly challenging when dealing with rare, diverse structures and complex sample preparation. Different metrics assess prediction reliability and offer insights into result strength, providing a comprehensive understanding of protein structure by combining different models. In a previous study, two proteins named ARM58 and ARM56 were investigated. These proteins contain four domains of unknown function and are present in Leishmania spp. ARM refers to an antimony resistance marker. The study's main objective is to assess the accuracy of the model's predictions, thereby providing insights into the complexities and supporting metrics underlying these findings. The analysis also extends to the comparison of predictions obtained from other species and organisms. Notably, one of these proteins shares an ortholog with Trypanosoma cruzi and Trypanosoma brucei, leading further significance to our analysis. This attempt underscored the importance of evaluating the diverse outputs from deep learning models, facilitating comparisons across different organisms and proteins. This becomes particularly pertinent in cases where no previous structural information is available.

Folding Kinetics and Volume Variation of the β-Hairpin Peptide Chignolin upon Ultrafast pH-Jumps

In-depth characterization of fundamental folding steps of small model peptides is crucial for a better understanding of the folding mechanisms of more complex biomacromolecules. We have previously reported on the folding/unfolding kinetics of a model α-helix. Here, we study folding transitions in chignolin (GYDPETGTWG), a short β-hairpin peptide previously used as a model to study conformational changes in β-sheet proteins. Although previously suggested, until now, the role of the Tyr2-Trp9 interaction in the folding mechanism of chignolin was not clear. In the present work, pH-dependent conformational changes of chignolin were characterized by circular dichroism (CD), nuclear magnetic resonance (NMR), ultrafast pH-jump coupled with time-resolved photoacoustic calorimetry (TR-PAC), and molecular dynamics (MD) simulations. Taken together, our results present a comprehensive view of chignolin's folding kinetics upon local pH changes and the role of the Tyr2-Trp9 interaction in the folding process. CD data show that chignolin's β-hairpin formation displays a pH-dependent skew bell-shaped curve, with a maximum close to pH 6, and a large decrease in β-sheet content at alkaline pH. The β-hairpin structure is mainly stabilized by aromatic interactions between Tyr2 and Trp9 and CH-π interactions between Tyr2 and Pro4. Unfolding of chignolin at high pH demonstrates that protonation of Tyr2 is essential for the stability of the β-hairpin. Refolding studies were triggered by laser-induced pH-jumps and detected by TR-PAC. The refolding of chignolin from high pH, mainly due to the protonation of Tyr2, is characterized by a volume expansion (10.4 mL mol-1), independent of peptide concentration, in the microsecond time range (lifetime of 1.15 μs). At high pH, the presence of the deprotonated hydroxyl (tyrosinate) hinders the formation of the aromatic interaction between Tyr2 and Trp9 resulting in a more disorganized and dynamic tridimensional structure of the peptide. This was also confirmed by comparing MD simulations of chignolin under conditions mimicking neutral and high pH.

Predicting drug-Protein interaction with deep learning framework for molecular graphs and sequences: Potential candidates against SAR-CoV-2

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) caused the COVID-19 disease, which represents a new life-threatening disaster. Regarding viral infection, many therapeutics have been investigated to alleviate the epidemiology such as vaccines and receptor decoys. However, the continuous mutating coronavirus, especially the variants of Delta and Omicron, are tended to invalidate the therapeutic biological product. Thus, it is necessary to develop molecular entities as broad-spectrum antiviral drugs. Coronavirus replication is controlled by the viral 3-chymotrypsin-like cysteine protease (3CLpro) enzyme, which is required for the virus's life cycle. In the cases of severe acute respiratory syndrome coronavirus (SARS-CoV) and middle east respiratory syndrome coronavirus (MERS-CoV), 3CLpro has been shown to be a promising therapeutic development target. Here we proposed an attention-based deep learning framework for molecular graphs and sequences, training from the BindingDB 3CLpro dataset (114,555 compounds). After construction of such model, we conducted large-scale screening the in vivo/vitro dataset (276,003 compounds) from Zinc Database and visualize the candidate compounds with attention score. geometric-based affinity prediction was employed for validation. Finally, we established a 3CLpro-specific deep learning framework, namely GraphDPI-3CL (AUROC: 0.958) achieved superior performance beyond the existing state of the art model and discovered 10 molecules with a high binding affinity of 3CLpro and superior binding mode.

Identification of domains in Plasmodium falciparum proteins of unknown function using DALI search on AlphaFold predictions

Plasmodium falciparum, the causative agent of malaria, poses a significant global health challenge, yet much of its biology remains elusive. A third of the genes in the P. falciparum genome lack annotations regarding their function, impeding our understanding of the parasite's biology. In this study, we employ structure predictions and the DALI search algorithm to analyse proteins encoded by uncharacterized genes in the reference strain 3D7 of P. falciparum. By comparing AlphaFold predictions to experimentally determined protein structures in the Protein Data Bank, we found similarities to known domains in 353 proteins of unknown function, shedding light on their potential functions. The lowest-scoring 5% of similarities were additionally validated using the size-independent TM-align algorithm, confirming the detected similarities in 88% of the cases. Notably, in over 70 P. falciparum proteins the presence of domains resembling heptatricopeptide repeats, which are typically involvement in RNA binding and processing, was detected. This suggests this family, which is important in transcription in mitochondria and apicoplasts, is much larger in Plasmodium parasites than previously thought. The results of this domain search provide a resource to the malaria research community that is expected to inform and enable experimental studies.

Unveiling the Mechanisms of EGCG-p53 Interactions through Molecular Dynamics Simulations

Green tea consumption is associated with protective and preventive effects against various types of cancer. These effects are attributed to polyphenols, particularly epigallocatechin-3-gallate (EGCG). EGCG acts by directly inhibiting tumor suppressor protein p53. The binding mechanism by which EGCG inhibits p53 activity is associated with residues Trp23-Lys24 and Pro47-Thr55 within the p53 N-terminal domain (NTD). However, the structural and thermodynamic aspects of the interaction between EGCG and p53 are poorly understood. Therefore, based on crystallographic data, we combine docking, molecular dynamics (MD) simulations, and molecular mechanics generalized Born surface area approaches to explore the intricacies of the EGCG-p53 binding mechanism. A triplicate microsecond MD simulation for each system is initially performed to capture diverse p53 NTD conformations. From the start, the most populated cluster of the second run (R2-1) stands out due to a unique opening between Trp23 and Trp53. During MD simulations, this conformation allows EGCG to sustain a high level of stability and affinity while interacting with both regions of interest and deepening the binding pocket. Structural analysis emphasizes the significance of pyrogallol motifs in EGCG binding. Therefore, the conformational shift in this gap is pivotal, enabling EGCG to impede p53 interactions and manifest its anticancer properties. These findings enhance the present comprehension of the anticancer properties of green tea polyphenols and pave the way for future therapeutic developments.

A unique approach for protein secondary structure comparison under TOPS representation

To unravel the intricate connection between protein function and protein structure, it is imperative to comprehensively evaluate protein secondary structure similarity from various perspectives. While numerous techniques have been suggested for comparing protein secondary structure elements (SSE), there continues to be a substantial need for finding alternative ways of comparing the same. In this paper, Topology of Protein Structure (TOPS) representations of protein secondary structures are considered to offer a new alignment-free method for evaluating similarities/dissimilarities of protein secondary structures. Initially, a two-dimensional numerical representation of the SSE is created, associating each point with a mass reflecting its frequency of occurrence. Then the means of coordinate values are determined by averaging weighted sums, and these mean values are subsequently used to calculate moments-of-inertia. Next, a four-component descriptor is generated out of the eigenvalues of the matrix and the mean values of the represented coordinates. Thereafter, Manhattan distance measure is used to obtain the distance matrix. This is finally applied to obtain the phylogenetic trees under the use of NJ method. SSE considered in the proposed method comprises 36-elements from the Chew-Kedem database giving five different taxa: globin, alpha-beta, tim-barrel, beta, and alpha. Phylogenetic trees were created for these SSE through the application of various methods: Clustal-Omega, LZ-Complexity, SED, TOPS + and TOC, to facilitate comparative analysis. Phylogenetic tree of the proposed method outperformed results of the previous methods when applied to the same SSE. Therefore, the method effectively constructs phylogenetic tree for analyzing protein secondary structure comparison.Communicated by Ramaswamy H. Sarma.

Identification of levomenthol derivatives as potential dipeptidyl peptidase-4 inhibitors: a comparative study with gliptins

Dipeptidyl peptidase-4 (DPP4) inhibitors are a potent therapeutic treatment for type 2 diabetes mellitus (T2DM). There is a family of compounds used as DPP4 inhibitors (DPP4Is) called gliptins. They bind tightly to DPP4 to form an inactive protein-ligand complex. However, there remains a need to identify novel DPP4Is that are more efficacious and safer due to the increasing prevalence of T2DM and the undesirable side effects of gliptins. To identify potential DPP4Is, we screened over 1800 novel compounds in a comparative study with gliptins. We performed dual-factor molecular docking to assess the binding affinity of the compounds to DPP4 and found four compounds with a higher binding affinity to DPP4 than currently used gliptins. The newly identified compounds interacted with the dyad glutamate (GLU205 and GLU206) and tyrosine (TYR662 and TYR666) residues in DPP4's active site. We performed molecular dynamics simulations to determine the stability of the protein-ligand complexes formed by the compounds and DPP4. Furthermore, we examined the toxicity and pharmacological profile of the compounds. The compounds are drug-like, easy to synthesize, and relatively less toxic than gliptins. Collectively, our results suggest that the novel compounds are potential DPP4Is and should be considered for further studies to develop novel antidiabetics.Communicated by Ramaswamy H. Sarma.

Investigating the Antiviral Properties of Nyctanthes arbor-tristis Linn against the Ebola, SARS-CoV-2, Nipah, and Chikungunya Viruses: A Computational Simulation Study

Background: The hunt for naturally occurring antiviral compounds to combat viral infection was expedited when COVID-19 and Ebola spread rapidly. Phytochemicals from Nyctanthes arbor-tristis Linn were evaluated as significant inhibitors of these viruses. Methods: Computational tools and techniques were used to assess the binding pattern of phytochemicals from Nyctanthes arbor-tristis Linn to Ebola virus VP35, SARS-CoV-2 protease, Nipah virus glycoprotein, and chikungunya virus. Results: Virtual screening and AutoDock analysis revealed that arborside-C, beta amyrin, and beta-sitosterol exhibited a substantial binding affinity for specific viral targets. The arborside-C and beta-sitosterol molecules were shown to have binding energies of -8.65 and -9.11 kcal/mol, respectively, when interacting with the major protease. Simultaneously, the medication remdesivir exhibited a control value of -6.18 kcal/mol. The measured affinity of phytochemicals for the other investigated targets was -7.52 for beta-amyrin against Ebola and -6.33 kcal/mol for nicotiflorin against Nipah virus targets. Additional molecular dynamics simulation (MDS) conducted on the molecules with significant antiviral potential, specifically the beta-amyrin-VP35 complex showing a stable RMSD pattern, yielded encouraging outcomes. Conclusions: Arborside-C, beta-sitosterol, beta-amyrin, and nicotiflorin could be established as excellent natural antiviral compounds derived from Nyctanthes arbor-tristis Linn. The virus-suppressing phytochemicals in this plant make it a compelling target for both in vitro and in vivo research in the future.

Characterization of a New Variant in ARHGAP31 Probably Involved in Adams-Oliver Syndrome in a Family with a Variable Phenotypic Spectrum

Adams-Oliver syndrome is a rare inherited condition characterized by scalp defects and limb abnormalities. It is caused by variants in different genes such as ARHGAP31. Here, we used an interdisciplinary approach to study a family with lower limb anomalies. We identified a novel variant in the ARHGAP31 gene that is predicted to result in a truncated protein with a constitutively activated catalytic site due to the loss of 688 amino acids involved in the C-terminal domain, essential for protein auto-inhibition. Pathogenic variants in ARHGAP31 exon 12, leading to a premature protein termination, are associated with Adams-Oliver syndrome. Bioinformatic analysis was useful to elucidate the impact of the identified genetic variant on protein structure. To better understand the impact of the identified variant, 3D protein models were predicted for the ARHGAP31 wild type, the newly discovered variant, and other pathogenetic alterations already reported. Our study identified a novel variant probably involved in Adams-Oliver syndrome and increased the evidence on the phenotypic variability in patients affected by this syndrome, underlining the importance of translational research, including experimental and bioinformatics analyses. This strategy represents a successful model to investigate molecular mechanisms involved in syndrome occurrence.

The monocyte cell surface is a unique site of autoantigen generation in rheumatoid arthritis

Although anti-citrullinated protein autoantibodies (ACPAs) are a hallmark serological feature of rheumatoid arthritis (RA), the mechanisms and cellular sources behind the generation of the RA citrullinome remain incompletely defined. Peptidylarginine deiminase IV (PAD4), one of the key enzymatic drivers of citrullination in the RA joint, is expressed by granulocytes and monocytes; however, the subcellular localization and contribution of monocyte-derived PAD4 to the generation of citrullinated autoantigens remain underexplored. In this study, we demonstrate that PAD4 displays a widespread cellular distribution in monocytes, including expression on the cell surface. Surface PAD4 was enzymatically active and capable of citrullinating extracellular fibrinogen and endogenous surface proteins in a calcium dose-dependent manner. Fibrinogen citrullinated by monocyte-surface PAD4 could be specifically recognized over native fibrinogen by a panel of eight human monoclonal ACPAs. Several unique PAD4 substrates were identified on the monocyte surface via mass spectrometry, with citrullination of the CD11b and CD18 components of the Mac-1 integrin complex being the most abundant. Citrullinated Mac-1 was found to be a target of ACPAs in 25% of RA patients, and Mac-1 ACPAs were significantly associated with HLA-DRB1 shared epitope alleles, higher C-reactive protein and IL-6 levels, and more erosive joint damage. Our findings implicate the monocyte cell surface as a unique and consequential site of extracellular and cell surface autoantigen generation in RA.

Antimicrobial activity of Geranyl acetate against cell wall synthesis proteins of P. aeruginosa and S. aureus using molecular docking and simulation

Incidences of Methicillin-Resistant Staphylococcus aureus and Multi-Drug Resistant Pseudomonas aeruginosa causing skin and soft tissue infections are becoming more prevalent due to repeated mutations and changes in the environment. Coriandrum sativum, a well-known Indian herbal medicinal plant, is shown to have antioxidant, antibacterial, and anti-inflammatory activity. This comparative study focuses on the molecular docking (PyRx v0.9.8) of ligand binding domains of WbpE Aminotransferase involved in O-antigen assembly in Pseudomonas aeruginosa (3NU7) and Beta-Lactamase found in Staphylococcus aureus (1BLC) with selected phytocompounds of Coriandrum sativum along with a known binder and a clinical reference drug. This was followed by molecular dynamics simulation studies (GROMACS v2019.4) for the docked complexes (with Geranyl acetate) with the best binding affinities (-23.4304 kJ/mol with Beta-Lactamase and -28.4512 kJ/mol with WbpE Aminotransferase) and maximum hydrogen bonds. Molecular dynamics simulation studies for both the proteins demonstrated that the complex with Geranyl acetate showed stability comparable to the complex with reference drug observed via Root Mean Square Deviation (RMSD), Root Mean Square Fluctuation (RMSF) and H-bond analyses. Changes in the secondary structural elements indicated that Geranyl acetate could possibly cause improper functioning of WbpE Aminotransferase leading to disrupted cell wall formation. Further, MM/PBSA analyses showed significant binding affinity of Geranyl acetate with WbpE Aminotransferase and Beta-Lactamase. This study aims to provide rationale for further studies of Coriandrum sativum as an antimicrobial, and to contextualise the results in the current scenario of growing antimicrobial resistance. HIGHLIGHTSPhytoconstituents present in Coriandrum sativum show significant binding affinity to the proteins in Pseudomonas aeruginosa and Staphylococcus aureus.Geranyl acetate exhibited the highest binding affinity with WbpE Aminotransferase involved in O-antigen assembly in Pseudomonas aeruginosa (PDB ID:3NU7) and Beta-Lactamase found in Staphylococcus aureus (PDB ID: 1BLC)Molecular dynamics simulation analyses show that the phytoconstituent, Geranyl acetate has an effect similar to the clinical reference drug, thus exhibiting potential antibacterial activity.Communicated by Ramaswamy H. Sarma.

Targeting Fks1 proteins for novel antifungal drug discovery

Fungal infections are a major threat to human health. The limited availability of antifungal drugs, the emergence of drug resistance, and a growing susceptible population highlight the critical need for novel antifungal agents. The enzymes involved in fungal cell wall synthesis offer potential targets for antifungal drug development. Recent studies have enhanced our focus on the enzyme Fks1, which synthesizes β-1,3-glucan, a critical component of the cell wall. These studies provide a deeper understanding of Fks1's function in cell wall biosynthesis, pathogenicity, structural biology, evolutionary conservation across fungi, and interaction with current antifungal drugs. Here, we discuss the role of Fks1 in the survival and adaptation of fungi, guided by insights from evolutionary and structural analyses. Furthermore, we delve into the dynamics of Fks1 modulation with novel antifungal strategies and assess its potential as an antifungal drug target.

ATOMDANCE: Kernel-based denoising and choreographic analysis for protein dynamic comparison

Comparative methods in molecular evolution and structural biology rely heavily upon the site-wise analysis of DNA sequence and protein structure, both static forms of information. However, it is widely accepted that protein function results from nanoscale nonrandom machine-like motions induced by evolutionarily conserved molecular interactions. Comparisons of molecular dynamics (MD) simulations conducted between homologous sites representative of different functional or mutational states can potentially identify local effects on binding interaction and protein evolution. In addition, comparisons of different (i.e., nonhomologous) sites within MD simulations could be employed to identify functional shifts in local time-coordinated dynamics indicative of logic gating within proteins. However, comparative MD analysis is challenged by the large fraction of protein motion caused by random thermal noise in the surrounding solvent. Therefore, properly denoised MD comparisons could reveal functional sites involving these machine-like dynamics with good accuracy. Here, we introduce ATOMDANCE, a user-interfaced suite of comparative machine learning-based denoising tools designed for identifying functional sites and the patterns of coordinated motion they can create within MD simulations. ATOMDANCE-maxDemon4.0 employs Gaussian kernel functions to compute site-wise maximum mean discrepancy between learned features of motion, thereby assessing denoised differences in the nonrandom motions between functional or evolutionary states (e.g., ligand bound versus unbound, wild-type versus mutant). ATOMDANCE-maxDemon4.0 also employs maximum mean discrepancy to analyze potential random amino acid replacements allowing for a site-wise test of neutral versus nonneutral evolution on the divergence of dynamic function in protein homologs. Finally, ATOMDANCE-Choreograph2.0 employs mixed-model analysis of variance and graph network to detect regions where time-synchronized shifts in dynamics occur. Here, we demonstrate ATOMDANCE's utility for identifying key sites involved in dynamic responses during functional binding interactions involving DNA, small-molecule drugs, and virus-host recognition, as well as understanding shifts in global and local site coordination occurring during allosteric activation of a pathogenic protease.

Impact of mutations on the stability of SARS-CoV-2 nucleocapsid protein structure

The nucleocapsid (N) protein of SARS-CoV-2 is known to participate in various host cellular processes, including interferon inhibition, RNA interference, apoptosis, and regulation of virus life cycles. Additionally, it has potential as a diagnostic antigen and/or immunogen. Our research focuses on examining structural changes caused by mutations in the N protein. We have modeled the complete tertiary structure of native and mutated forms of the N protein using Alphafold2. Notably, the N protein contains 3 disordered regions. The focus was on investigating the impact of mutations on the stability of the protein's dimeric structure based on binding free energy calculations (MM-PB/GB-SA) and RMSD fluctuations after MD simulations. The results demonstrated that 28 mutations out of 37 selected mutations analyzed, compared with wild-type N protein, resulted in a stable dimeric structure, while 9 mutations led to destabilization. Our results are important to understand the tertiary structure of the N protein dimer of SARS-CoV-2 and the effect of mutations on it, their behavior in the host cell, as well as for the research of other viruses belonging to the same genus additionally, to anticipate potential strategies for addressing this viral illness․.

Galectin-3 - A novel ligand of complement protein C1q

In the present study we report a novel interaction of human C1q, a primary activator of the Complement system, with human Galectin-3 (Gal-3). We investigated the potential recognition between C1q and Gal-3 on a solid hydrophobic surface by ELISA, by fluorescence spectroscopy, molecular docking and molecular dynamics (MD). The data showed that C1q and Gal-3 had a pronounced affinity for protein-protein interaction and supramolecular binding, locating the binding sites within the globular domains of C1q (gC1q) and on the backside of the carbohydrate recognition domain (CRD) of Gal-3. Fluorescence spectroscopy gave quantitative assessment of the recognition with KD value of 0.04 μM. MD analysis showed that when the active AAs of the two proteins interacted, electrostatic attraction, aided by a large number of hydrogen bonds, was dominant for the stabilization of the complex. When the contact of C1q and Gal-3 was not limited to active residues, the complex between them was stabilized mainly by Van der Waals interactions and smaller in number but stronger hydrogen bonds. This is the first report analyzing the interaction of Gal-3 with C1q, which could open the way to new applications of this protein-protein complex.

Identification of Residues Potentially Involved in Optical Shifts in the Water-Soluble Chlorophyll a-Binding Protein through Molecular Dynamics Simulations

Reversible light and thermally induced spectral shifts are universally observed in a wide variety of pigment-protein complexes at temperatures ranging from cryogenic to ambient. In this paper, we employed large-scale molecular dynamics (MD) simulations of a prototypical pigment-protein complex to better understand these shifts at a molecular scale. Although multiple mechanisms have been proposed over the years, no verification of these proposals via MD simulations has thus far been performed; our work represents the first step in this direction. From simulations of the water-soluble chlorophyll-binding protein complex, we determined that rearrangements of long hydrogen bonds were unlikely to be the origin of the multiwell landscape features necessary to explain observed spectral shifts. We also assessed small motions of amino acid residues and identified side chain rotations of some of these residues as likely candidates for the origin of relevant multiwell landscape features. The protein free-energy landscapes associated with side chain rotations feature energy barriers of around 1100-1600 cm-1, in agreement with optical spectroscopy results, with the most promising residue type associated with experimental signatures being serine, which possesses a symmetric triple-well landscape and moment of inertia of a relevant magnitude.

Exploring promising natural compounds for breast cancer treatment: in silico molecular docking targeting WDR5-MYC protein interaction

Cancer is an aberrant differentiation of normal cells, characterized by uncontrolled growth and the potential to acquire invasive and aggressive properties that ultimately lead to metastasis. In the realm of scientific exploration, a multitude of pathways has been investigated and targeted by researchers, among which one specific pathway is recognized as WDR5-MYC. Continuous investigations and research show that WDR5-MYC is a therapeutic target protein. Hence, the discovery of naturally occurring compounds with anticancer properties has been suggested as a rapid and efficient alternative for the development of anticancerous therapeutics. A virtual screening approach was used to identify the most potent compounds from the NP-lib database at the MTiOpenScreen webserver against WDR5-MYC. This process yielded a total of 304 identified compounds. Subsequently, after screening, four potent compounds, namely Estrone (ZINC000003869899), Ethyl-1,2-benzanthracene (ZINC000003157052), Strychnine (ZINC000000119434) and 7H-DIBENZO [C, G] CARBAZOLE (ZINC000001562130), along with a cocrystallized 5-[4-(trifluoromethyl) phenyl]-1H-tetrazole inhibitor (QBP) as a reference ligand, were considered for stringent molecular docking. Thus, each compound exhibited significant docking energy between -8.2 and -7.7 kcal/mol and molecular contacts with essential residue Asn225, Lys250, Ser267 and Lys272 in the active pocket of WDR5-MYC against the QBP inhibitor (the native ligand QBP serves as a reference in the comparative analysis of docked complexes). The results support the potent compounds for drug-likeness and strong binding affinity with WDR5-MYC protein. Further, the stability of the selected compounds was predicted by molecular dynamics simulation (100 ns) contributed by intermolecular hydrogen bonds and hydrophobic interactions. This demonstrates the potential of the selected compounds to be used against breast cancer treatment.Communicated by Ramaswamy H. Sarma.

Identification of potential inhibitor against Leishmania donovani mitochondrial DNA primase through in-silico and in vitro drug repurposing approaches

Leishmania donovani is the causal organism of leishmaniasis with critical health implications affecting about 12 million people around the globe. Due to less efficacy, adverse side effects, and resistance, the available therapeutic molecules fail to control leishmaniasis. The mitochondrial primase of Leishmania donovani (LdmtPRI1) is a vital cog in the DNA replication mechanism, as the enzyme initiates the replication of the mitochondrial genome of Leishmania donovani. Hence, we target this protein as a probable drug target against leishmaniasis. The de-novo approach enabled computational prediction of the three-dimensional structure of LdmtPRI1, and its active sites were identified. Ligands from commercially available drug compounds were selected and docked against LdmtPRI1. The compounds were chosen for pharmacokinetic study and molecular dynamics simulation based on their binding energies and protein interactions. The LdmtPRI1 gene was cloned, overexpressed, and purified, and a primase activity assay was performed. The selected compounds were verified experimentally by the parasite and primase inhibition assay. Capecitabine was observed to be effective against the promastigote form of Leishmania donovani, as well as inhibiting primase activity. This study's findings suggest capecitabine might be a potential anti-leishmanial drug candidate after adequate further studies.

Searching for Structure: Characterizing the Protein Conformational Landscape with Clustering-Based Algorithms

The identification and characterization of the main conformations from a protein population are a challenging and inherently high-dimensional problem. Here, we evaluate the performance of the Secondary sTructural Ensembles with machine LeArning (StELa) double-clustering method, which clusters protein structures based on the relationship between the φ and ψ dihedral angles in a protein backbone and the secondary structure of the protein, thus focusing on the local properties of protein structures. The classification of states as vectors composed of the clusters' indices arising naturally from the Ramachandran plot is followed by the hierarchical clustering of the vectors to allow for the identification of the main features of the corresponding free energy landscape (FEL). We compare the performance of StELa with the established root-mean-squared-deviation (RMSD)-based clustering algorithm, which focuses on global properties of protein structures and with Combinatorial Averaged Transient Structure (CATS), the combinatorial averaged transient structure clustering method based on distributions of the φ and ψ dihedral angle coordinates. Using ensembles of conformations from molecular dynamics simulations of intrinsically disordered proteins (IDPs) of various lengths (tau protein fragments) or short fragments from a globular protein, we show that StELa is the clustering method that identifies many of the minima and relevant energy states around the minima from the corresponding FELs. In contrast, the RMSD-based algorithm yields a large number of clusters that usually cover most of the FEL, thus being unable to distinguish between states, while CATS does not sample well the FELs for long IDPs and fragments from globular proteins.

A computational strategy for systematic virtual screening of plasmodium falciparum heme detoxification protein inhibitors from the Drugbank database

Antimalarial drug resistance poses one of the greatest threats to malaria treatment, resulting in increased morbidity and mortality. Heme Detoxification Protein (HDP) is among the essential hemoglobinases of P. falciparum (Pf), a vital molecular target for the treatment of malaria. In this study, we utilized the virtual screening workflow tool of the Schrodinger suite to find the best hits for the PfHDP from the DrugBank library. A total of 14,942 compounds were identified against the PfHDP. The top compounds with the highest docking scores and least energy scores were subjected to molecular simulations for 500 nanosecond to check the stability of the protein-drug complexes. The top three DrugBank compounds were found to be stable over 500 ns, namely DB09298 (silibinin), DB07426 (1-Hydroxy-2-(1,1':3',1''-Terphenyl-3-Yloxy) Ethane-1,1-Diyl] Bis (Phosphonic Acid), and DB07410 [(2-(3-Dibenzofuran-4-yl-Phenyl)-1-Hydroxy-1-Phosphono-Ethyl]-Phosphonic Acid). Overall analysis suggests that the top three compounds, DB09298, DB07426, and DB07410, have good stability for 500 ns. Their scaffolds can be used to design and develop new analogs of the target HDP protein. Silibinin, the anti-cancer drug, was found to be highly stable for the entire simulation period as compared to the other compounds. DB07426 shows its therapeutic effect on bones, especially in the treatment of osteoporosis, and DB07410 has anti-tumor, antibacterial, anti-oxidative, and anti-viral activities. All three compounds can be considered for repurposing as antimalarial drugs to evaluate the binding capacity or inhibition potential of these compounds. Further in-vivo and in-vitro analysis against the PfHDP protein should be conducted.Communicated by Ramaswamy H. Sarma.

Bitter taste receptors establish a stable binding affinity with the SARS-CoV-2-spike 1 protein akin to ACE2

COVID-19 is caused by the highly contagious SARS-CoV-2 virus, which originated in Wuhan, China, resulting in the highest worldwide mortality rate. Gustatory dysfunction is common among individuals infected with the Wild-type Wuhan strain. However, there are no reported cases of gustatory dysfunction among patients infected with the mutant delta variant. The reason behind this remains elusive to date. This in-silico-based study aims to unravel this clinical factor by evaluating the overall binding affinity of predominant bitter taste receptors associated with gustatory function (T2R-4, 10, 14, 19, 31, 38, 43, and 46) with the Receptor Binding Domain (RBD) of spike 1 (S1) protein of Wuhan (Wild)/delta-SARS-CoV-2 (mut1-T478K; mut2-E484K) variants. Based on docking and MM/PBSA free binding energy scores, the Wild RBD showed a stronger interaction with T2R-46 compared to the ACE2 protein. However, both delta variant mutants (mut1 and mut2) could not establish a stronger binding affinity with bitter taste receptor proteins, except for T2R-43 against mut1. In conclusion, the delta variants could not establish a better binding affinity with bitter taste receptors, contradicting the Wild variant that determines the severity of gustatory dysfunction among patients exposed to the delta and Wild SARS-CoV-2 variants. The study's inference also proposes T2R-46 as an alternate binding receptor target for RBD-S1 of Wild SARS-CoV-2, augmenting its virulence in all functional organs with compromised α-gustducin interaction and bitter sensitization. This in-silico-based study needs further wet-lab-based validation for a better understanding of the role of T2R-46-based viral entry in the human host.Communicated by Ramaswamy H. Sarma.

Integrated computational approach identifies potential inhibitors of ASK1-(JNK/P38) interaction signaling: new insights into cancer therapeutics

Cancers are characterized by the aberrant expression of certain genes that trigger a cascade of molecular events that culminate in dysregulated cell division. Consequently, the inhibition of the products of these expressedgenes has emerged as a rational approach in cancer therapy. The apoptosis signal-regulating kinase 1 (ASK1) protein, encoded by the mitogen-activated protein kinase kinase kinase 5 (MAP3K5) gene, plays pertinent roles in the mediation of cell death induced by stress and inflammation, andis often found at elevated levels in cancer. Consequently, it has emerged as a molecular target for the development of potential chemotherapeutics through identification of selective inhibitors. However, there is still dearth of ASK1 inhibitors in clinical use. Hence, molecular modelling approaches were employed in this study to discover potential ASK1 inhibitors from phytochemicals. Twenty-five phytocompounds from four medicinal plants were tested for their inhibitory prowess via molecular docking. Interestingly, all the compounds exhibited promising inhibitory potentials for ASK1. However, further subjection to filtering procedures via different pipelines including drug-likeness evaluation, pharmacokinetics screening, toxicity profiling, and better affinities compared to the approved inhibitor resulted in three hit compounds namely ellagic acid, luteolin, and kaempferol with suitable properties. Profiling of the interactions formed between the hit\compounds and the targets revealed several interactions that were not present in that of the approved inhibitor, while molecular dynamics (MD) simulation revealed the complexes formed as stable. Conclusively, this study identified three compounds with ASK1 inhibitory potentials that are worthy of further exploration in in vitro and in vivo studies.Communicated by Ramaswamy H. Sarma.

Do antibody CDR loops change conformation upon binding?

Antibodies have increasingly been developed as drugs with over 100 now licensed in the US or EU. During development, it is often necessary to increase or reduce the affinity of an antibody and rational attempts to do so rely on having a structure of the antibody-antigen complex often obtained by modeling. The antigen-binding site consists primarily of six loops known as complementarity-determining regions (CDRs), and an open question has been whether these loops change their conformation when they bind to an antigen. Existing surveys of antibody-antigen complex structures have only examined CDR conformational change in case studies or small-scale surveys. With an increasing number of antibodies where both free and complexed structures have been deposited in the Protein Data Bank, a large-scale survey of CDR conformational change during binding is now possible. To this end, we built a dataset, AbAgDb, that currently includes 177 antibodies with high-quality CDRs, each of which has at least one bound and one unbound structure. We analyzed the conformational change of the Cα backbone of each CDR upon binding and found that, in most cases, the CDRs (other than CDR-H3) show minimal movement, while 70.6% and 87% of CDR-H3s showed global Cα RMSD ≤ 1.0Å and ≤ 2.0Å, respectively. We also compared bound CDR conformations with the conformational space of unbound CDRs and found most of the bound conformations are included in the unbound conformational space. In future, our results will contribute to developing insights into antibodies and new methods for modeling and docking.

Palmitoylation of the Glucagon-like Peptide-1 Receptor Modulates Cholesterol Interactions at the Receptor-Lipid Microenvironment

The G protein-coupled receptor (GPCR) superfamily of cell surface receptors has been shown to be functionally modulated by post-translational modifications. The glucagon-like peptide receptor-1 (GLP-1R), which is a drug target in diabetes and obesity, undergoes agonist-dependent palmitoyl tail conjugation. The palmitoylation in the C-terminal domain of GLP-1R has been suggested to modulate the receptor-lipid microenvironment. In this work, we have performed coarse-grain molecular dynamics simulations of palmitoylated and nonpalmitoylated GLP-1R to analyze the differential receptor-lipid interactions. Interestingly, the placement and dynamics of the C-terminal domain of GLP-1R are found to be directly dependent on the palmitoyl tail. We observe that both cholesterol and phospholipids interact with the receptor but display differential interactions in the presence and absence of the palmitoyl tail. We characterize important cholesterol-binding sites and validate sites that have been previously reported in experimentally resolved structures of the receptor. We show that the receptor acts like a conduit for cholesterol flip-flop by stabilizing cholesterol in the membrane core. Taken together, our work represents an important step in understanding the molecular effects of lipid modifications in GPCRs.

Network pharmacology, molecular docking and molecular dynamics simulation of chalcone scaffold-based compounds targeting breast cancer receptors

Compounds with a chalcone scaffold-based structure have demonstrated promising anticancer biological activity. However, the molecular interactions between chalcone scaffold-based compounds and breast cancer-associated proteins remain unclear. Through network pharmacology, molecular docking, and molecular dynamics (MD) simulation analyses, compounds with a chalcone scaffold-based structure were evaluated for their interaction with potential breast cancer targets. The compounds were retrieved from the ASINEX database, resulting in 575,302 compounds. A total of 342 compounds with chalcone scaffold-based structures were discovered. From the 342 compounds that was analysed, ten were chosen due to their adherence to Lipinski's rule, having an appropriate range of lipophilicity (LOGP), and topological polar surface area (TPSA), and absence of any toxicity. Based on target intersection, 50 target genes were found and subjected to protein-protein interaction (PPI), gene ontology (GO), and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses. Four target genes were found to be involved in the breast cancer pathway. Consequently, molecular docking was utilised to analyse the molecular interactions between the compounds and four target protein receptors. Compound 211 exhibited the highest binding affinities for the epidermal growth factor receptor (EGFR), fibroblast growth factor receptor 1 (FGFR1), oestrogen receptor (ESR1), and cyclin dependent kinase 6 (CDK6) with values of -8.95 kcal/mol, -8.60 kcal/mol, -10.33 kcal/mol, and -9.90 kcal/mol, respectively. During MD simulation, compound 211 and its respective proteins were stable, compact, and had minimal flexibility. The findings provide foundations for future studies into the interaction underlying the anti-breast cancer potential of compounds with chalcone-based scaffold structures.Communicated by Ramaswamy H. Sarma.

Computational Molecular Docking and Simulation-Based Assessment of Anti-Inflammatory Properties of Nyctanthes arbor-tristis Linn Phytochemicals

The leaves, flowers, seeds, and bark of the Nyctanthes arbor-tristis Linn plant have been pharmacologically evaluated to signify the medicinal importance traditionally described for various ailments. We evaluated the anti-inflammatory potentials of 26 natural compounds using AutoDock 4.2 and Molecular Dynamics (MDS) performed with the GROMACS tool. SwissADME evaluated ADME (adsorption, distribution, metabolism, and excretion) parameters. Arb_E and Beta-sito, natural compounds of the plant, showed significant levels of binding affinity against COX-1, COX-2, PDE4, PDE7, IL-17A, IL-17D, TNF-α, IL-1β, prostaglandin E2, and prostaglandin F synthase. The control drug celecoxib exhibited a binding energy of -9.29 kcal/mol, and among the tested compounds, Arb_E was the most significant (docking energy: -10.26 kcal/mol). Beta_sito was also observed with high and considerable docking energy of -8.86 kcal/mol with the COX-2 receptor. COX-2 simulation in the presence of Arb_E and control drug celecoxib, RMSD ranged from 0.15 to 0.25 nm, showing stability until the end of the simulation. Also, MM-PBSA analysis showed that Arb_E bound to COX-2 exhibited the lowest binding energy of -277.602 kJ/mol. Arb_E and Beta_sito showed interesting ADME physico-chemical and drug-like characteristics with significant drug-like effects. Therefore, the studied natural compounds could be potential anti-inflammatory molecules and need further in vitro/in vivo experimentation to develop novel anti-inflammatory drugs.

NADP+ or CO2 reduction by frhAGB-encoded hydrogenase through interaction with formate dehydrogenase 3 in the hyperthermophilic archaeon Thermococcus onnurineus NA1

IMPORTANCE

The strategy using structural homology with the help of structure prediction by AlphaFold was very successful in finding potential targets for the frhAGB-encoded hydrogenase of Thermococcus onnurineus NA1. The finding that the hydrogenase can interact with FdhB to reduce the cofactor NAD(P)+ is significant in that the enzyme can function to supply reducing equivalents, just as F420-reducing hydrogenases in methanogens use coenzyme F420 as an electron carrier. Additionally, it was identified that T. onnurineus NA1 could produce formate from H2 and CO2 by the concerted action of frhAGB-encoded hydrogenase and formate dehydrogenase Fdh3.

Secretory protein Rv1987, a 'probable chitinase' from Mycobacterium tuberculosis is a novel chitin and cellulose binding protein lacking enzymatic function

Bacterial chitinases serve to hydrolyse chitin as food source or as defence mechanism. Given that chitin is not produced by mammals, it is intriguing that Mycobacterium tuberculosis, an exclusively human pathogen harbours Rv1987, a probable chitinase and secretes it. Interestingly genes annotated as chitinases are widely distributed among Mycobacterium tuberculosis complex species, clinical isolates and other human pathogens M. abscessus and M. ulcerans. However, Mycobacterial chitinases are not characterized and hence the functions remain unknown. In the present study, we show that Rv1987 is a chitin and cellulose binding protein lacking enzymatic activity in contrary to its current annotation. Further, we show Rv1987 has moon lighting functions in M. tuberculosis pathobiology signifying roles of bacterial cellulose binding clusters in infections.

In silico and in vivo anti-angiogenic validation on ethanolic extract of Curcuma longa and curcumin compound in hepatocellular carcinoma through mitogen activated protein kinase expression in male and female wistar rats

Hepatocellular carcinoma (HCC) is the most frequent primary malignancy of the liver. The aim of this study is to evaluate the comparative in silico and in vivo ameliorative potential of the ethanolic extract of Curcuma longa (EECL) in male and female Wistar rats administered N-nitrosodiethylamine-induced hepatocellular carcinoma. The MAPK compound was obtained from a protein data bank (PDB ID: 7AUV) for molecular docking. One hundred and twenty Wistar rats, were randomly selected into twelve groups (n = 5): Group A received regular diets as a basal control; groups B to G were administered 100 mg/kg NDEA twice in two weeks; while groups C to E received 200 mg/kg, 400 mg/kg, and 600 mg/kg of EECL; group F was treated with 200 mg/kg pure curcumin; and group G received 100 mg/kg Sylibon-140. Group H received only 200 mg/kg pure curcumin, and group I received 200 mg/kg of dimethylsulfoxide (DMSO). Groups J, K, and L received 200 mg/kg, 400 mg/kg and 600 mg/kg of EECL. MAPK and AFP mRNA in Wistar rats administered NDEA were upregulated as compared to EECL groups. In conclusion, the in silico and in vitro study validates the mitigating role of ethanolic extract of Curcuma longa and pure curcumin.

Computational biology of antibody epitope, tunnels and pores analysis of protein glutathione S-transferase P, and quantum mechanics

Different tissues of various plants contain allelochemicals such as phenolics, flavonoids, etc., which exhibit antioxidants and protect the plants from harmful infections. The widespread group of plant allelochemicals in the ecosystem is phenolic compounds. They are substances composed of an aromatic hydrocarbon group and a hydroxyl group. The 3-Hydroxyflavone skeleton of flavonol has a phenolic and a hydroxyl substitution. A comparison of experimental and calculated data of FT-IR and Raman was studied for the vibrational assessment of these allelochemicals. PES scan and molecular geometry analysis are done for the conformation of the 3-Hydroxyflavone ligand. 3-Hydroxyflavone is docked with the three proteins of Homo sapiens such as Prothrombin with 622 amino acids synthesized in the liver, human neutrophils found within intracellular granules with 467 amino acids, Glutathione S-transferase P is produced from exogenous xenobiotics with 210 amino acids. The active site residues by using the Prothrombin (1A2C), Neutrophil collagenase (1A86), Glutathione S-transferase P(18 GS) protein with ligand 3-Hydroxyflavone, fair binding affinity was found for the Glutathione S-transferase P (18 GS). The MOLE online server web interface's ability to see and analyze tunnels and pores allows for simple, online interaction with bio-macromolecule investigation. The automatic transmembrane channel calculation on the MOLE web generates the quickest list of ligands for transport analysis and tunnel identification. Pore-forming proteins (PFPs) are recognized as crucial agents in immunity and infection. They target membranes by opening channels through them. ElliPro is thought to be a potentially effective method for identifying antibody epitopes in protein antigens. Molecular dynamics result the general time-dependent structural deviation/degree of similarity among the structures that the trajectory records. The epitope technique sought to examine the effectiveness of its web tool on linear and discontinuous epitopes known from the structures of antibodies of 18 GS with 3-Hydroxyflavone complexes and find effective scores.

Molecular Dynamics and Docking Simulations of Homologous RsmE Methyltransferases Hints at a General Mechanism for Substrate Release upon Uridine Methylation on 16S rRNA

In this study, molecular dynamics (MD) and docking simulations were carried out on the crystal structure of Neisseria Gonorrhoeae RsmE aiming at free energy of binding estimation (ΔGbinding) of the methyl transfer substrate S-adenosylmethionine (SAM), as well as its homocysteine precursor S-adenosylhomocysteine (SAH). The mechanistic insight gained was generalized in view of existing homology to two other crystal structures of RsmE from Escherichia coli and Aquifex aeolicus. As a proof of concept, the crystal poses of SAM and SAH were reproduced reflecting a more general pattern of molecular interaction for bacterial RsmEs. Our results suggest that a distinct set of conserved residues on loop segments between β12, α6, and Met169 are interacting with SAM and SAH across these bacterial methyltransferases. Comparing molecular movements over time (MD trajectories) between Neisseria gonorrhoeae RsmE alone or in the presence of SAH revealed a hitherto unknown gatekeeper mechanism by two isoleucine residues, Ile171 and Ile219. The proposed gating allows switching from an open to a closed state, mimicking a double latch lock. Additionally, two key residues, Arg221 and Thr222, were identified to assist the exit mechanism of SAH, which could not be observed in the crystal structures. To the best of our knowledge, this study describes for the first time a general catalytic mechanism of bacterial RsmE on theoretical ground.

Intrinsic self-organization of integrin nanoclusters within focal adhesions is required for cellular mechanotransduction

Upon interaction with the extracellular matrix, the integrin receptors form nanoclusters as a first biochemical response to ligand binding. Here, we uncover a critical biodesign principle where these nanoclusters are spatially self-organized, facilitating effective mechanotransduction. Mouse Embryonic Fibroblasts (MEFs) with integrin β3 nanoclusters organized themselves with an intercluster distance of ∼550 nm on uniformly coated fibronectin substrates, leading to larger focal adhesions. We determined that this spatial organization was driven by cell-intrinsic factors since there was no pre-existing pattern on the substrates. Altering this spatial organization using cyclo-RGD functionalized Titanium nanodiscs (of 100 nm, corroborating to the integrin nanocluster size) spaced at intervals of 300 nm (almost half), 600 nm (normal) or 1000 nm (almost double) resulted in abrogation in mechanotransduction, indicating that a new parameter i.e., an optimal intercluster distance is necessary for downstream function. Overexpression of α-actinin, which induces a kink in the integrin tail, disrupted the establishment of the optimal intercluster distance, while simultaneous co-overexpression of talin head with α-actinin rescued it, indicating a concentration-dependent competition, and that cytoplasmic activation of integrin by talin head is required for the optimal intercluster organization. Additionally, talin head-mediated recruitment of FHOD1 that facilitates local actin polymerization at nanoclusters, and actomyosin contractility were also crucial for establishing the optimal intercluster distance and a robust mechanotransduction response. These findings demonstrate that cell-intrinsic machinery plays a vital role in organizing integrin receptor nanoclusters within focal adhesions, encoding essential information for downstream mechanotransduction signalling.

α-Aminophosphonate inhibitors of metallo-β-lactamases NDM-1 and VIM-2

The upswing of antibiotic resistance is an escalating threat to human health. Resistance mediated by bacterial metallo-β-lactamases is of particular concern as these enzymes degrade β-lactams, our most frequently prescribed class of antibiotics. Inhibition of metallo-β-lactamases could allow the continued use of existing β-lactam antibiotics, such as penicillins, cephalosporins and carbapenems, whose applicability is becoming ever more limited. The design, synthesis, and NDM-1, VIM-2, and GIM-1 inhibitory activities (IC50 4.1-506 μM) of a series of novel non-cytotoxic α-aminophosphonate-based inhibitor candidates are presented herein. We disclose the solution NMR spectroscopic and computational investigation of their NDM-1 and VIM-2 binding sites and binding modes. Whereas the binding modes of the inhibitors are similar, VIM-2 showed a somewhat higher conformational flexibility, and complexed a larger number of inhibitor candidates in more varying binding modes than NDM-1. Phosphonate-type inhibitors may be potential candidates for development into therapeutics to combat metallo-β-lactamase resistant bacteria.

Pharmacophore mapping approach to find anti-cancer phytochemicals with metformin-like activities against transforming growth factor (TGF)-beta receptor I kinase: An in silico study

The most frequently prescribed first-line treatment for type II diabetes mellitus is metformin. Recent reports asserted that this diabetes medication can also shield users from cancer. Metformin induces cell cycle arrest in cancer cells. However, the exact mechanism by which this occurs in the cancer system is yet to be elucidated. Here, we investigated the impact of metformin on cell cycle arrest in cancer cells utilizing transforming growth factor (TGF)-beta pathway. TGF-ß pathway has significant effect on cell progression and growth. In order to gain an insight on the underlying molecular mechanism of metformin's effect on TGF beta receptor 1 kinase, molecular docking was performed. Metformin was predicted to interact with transforming growth factor (TGF)-beta receptor I kinase based on molecular docking and molecular dynamics simulations. Furthermore, pharmacophore was generated for metformin-TGF-ßR1 complex to hunt for novel compounds having similar pharmacophore as metformin with enhanced anti-cancer potentials. Virtual screening with 29,000 natural compounds from NPASS database was conducted separately for the generated pharmacophores in Ligandscout® software. Pharmacophore mapping showed 60 lead compounds for metformin-TGF-ßR1 complex. Molecular docking, molecular dynamics simulation for 100 ns and ADMET analysis were performed on these compounds. Compounds with CID 72473, 10316977 and 45140078 showed promising binding affinities and formed stable complexes during dynamics simulation with aforementioned protein and thus have potentiality to be developed into anti-cancer medicaments.

An In Silico Multi-epitopes Vaccine Ensemble and Characterization Against Nosocomial Proteus penneri

Proteus penneri (P. penneri) is a bacillus-shaped, gram-negative, facultative anaerobe bacterium that is primarily an invasive pathogen and the etiological agent of several hospital-associated infections. P. penneri strains are naturally resistant to macrolides, amoxicillin, oxacillin, penicillin G, and cephalosporins; in addition, no vaccines are available against these strains. This warrants efforts to propose a theoretical based multi-epitope vaccine construct to prevent pathogen infections. In this research, reverse vaccinology bioinformatics and immunoinformatics approaches were adopted for vaccine target identification and construction of a multi-epitope vaccine. In the first phase, a core proteome dataset of the targeted pathogen was obtained using the NCBI database and subjected to bacterial pan-genome analysis using bacterial pan-genome analysis (BPGA) to predict core protein sequences which were then used to find good vaccine target candidates. This identified two proteins, Hcp family type VI secretion system effector and superoxide dismutase family protein, as promising vaccine targets. Afterward using the IEDB database, different B-cell and T-cell epitopes were predicted. A set of four epitopes "KGSVNVQDRE, NTGKLTGTR, IIHSDSWNER, and KDGKPVPALK" were chosen for the development of a multi-epitope vaccine construct. A 183 amino acid long vaccine design was built along with "EAAAK" and "GPGPG" linkers and a cholera toxin B-subunit adjuvant. The designed vaccine model comprised immunodominant, non-toxic, non-allergenic, and physicochemical stable epitopes. The model vaccine was docked with MHC-I, MHC-II, and TLR-4 immune cell receptors using the Cluspro2.0 web server. The binding energy score of the vaccine was - 654.7 kcal/mol for MHC-I, - 738.4 kcal/mol for MHC-II, and - 695.0 kcal/mol for TLR-4. A molecular dynamic simulation was done using AMBER v20 package for dynamic behavior in nanoseconds. Additionally, MM-PBSA binding free energy analysis was done to test intermolecular binding interactions between docked molecules. The MM-GBSA net binding energy score was - 148.00 kcal/mol, - 118.00 kcal/mol, and - 127.00 kcal/mol for vaccine with TLR-4, MHC-I, and MHC-II, respectively. Overall, these in silico-based predictions indicated that the vaccine is highly promising in terms of developing protective immunity against P. penneri. However, additional experimental validation is required to unveil the real immune response to the designed vaccine.

Role of α2δ-3 in regulating calcium channel localization at presynaptic active zones during homeostatic plasticity

The homeostatic modulation of synaptic transmission is an evolutionarily conserved mechanism that is critical for stabilizing the nervous system. At the Drosophila neuromuscular junction (NMJ), presynaptic homeostatic potentiation (PHP) compensates for impairments in postsynaptic glutamate receptors due to pharmacological blockade or genetic deletion. During PHP, there is an increase in presynaptic neurotransmitter release, counteracting postsynaptic changes and restoring excitation to baseline levels. Previous studies have shown that α2δ-3, an auxiliary subunit of voltage-gated calcium channels (VGCCs), is essential for both the rapid induction and sustained expression of PHP at the Drosophila NMJ. However, the molecular mechanisms by which α2δ-3 regulates neurotransmitter release during PHP remain to be elucidated. In this study, we utilized electrophysiological, confocal imaging, and super-resolution imaging approaches to explore how α2δ-3 regulates synaptic transmission during PHP. Our findings suggest that α2δ-3 governs PHP by controlling the localization of the calcium channel pore-forming α1 subunit at presynaptic release sites, or active zones. Moreover, we examined the role of two structural domains within α2δ-3 in regulating neurotransmitter release and calcium channel localization. Our results highlight that these domains in α2δ-3 serve distinct functions in controlling synaptic transmission and presynaptic calcium channel abundance, at baseline in the absence of perturbations and during PHP. In summary, our research offers compelling evidence that α2δ-3 is an indispensable signaling component for controlling calcium channel trafficking and stabilization in homeostatic plasticity.

Exploring the interactions of antihistamine with retinoic acid receptor beta (RARB) by molecular dynamics simulations and genome-wide meta-analysis

Kaposi sarcoma (KS) is one of the most common AIDS-related malignant neoplasms, which can leave lesions on the skin among HIV patients. These lesions can be treated with 9-cis-retinoic acid (9-cis-RA), an endogenous ligand of retinoic acid receptors that has been FDA-approved for treatment of KS. However, topical application of 9-cis-RA can induce several unpleasant side effects, like headache, hyperlipidemia, and nausea. Hence, alternative therapeutics with less side effects are desirable. There are case reports associating over-the-counter antihistamine usage with regression of KS. Antihistamines competitively bind to H1 receptor and block the action of histamine, best known for being released in response to allergens. Furthermore, there are already dozens of antihistamines that are FDA-approved with less side effects than 9-cis-RA. This led our team to conduct a series of in-silico assays to determine whether antihistamines can activate retinoic acid receptors. First, we utilized high-throughput virtual screening and molecular dynamics simulations to model high-affinity interactions between antihistamines and retinoic acid receptor beta (RARβ). We then performed systems genetics analysis to identify a genetic association between H1 receptor itself and molecular pathways involved in KS. Together, these findings advocate for exploration of antihistamines against KS, starting with our two promising hit compounds, bepotastine and hydroxyzine, for experimental validation study in the future.

Computational modelling of potential Zn-sensitive non-β-lactam inhibitors of imipenemase-1 (IMP-1)

Antibiotic resistance (AR) remains one of the leading global health challenges, mostly implicated in disease-related deaths. The Enterobacteriaceae-producing metallo-β-lactamases (MBLs) are critically involved in AR pathogenesis through Zn-dependent catalytic destruction of β-lactam antibiotics, yet with limited successful clinical inhibitors. The efficacy of relevant broad-spectrum β-lactams including imipenem and meropenem are seriously challenged by their susceptibility to the Zn-dependent carbapenemase hydrolysis, as such, searching for alternatives remains imperative. In this study, computational molecular modelling and virtual screening methods were extensively applied to identify new putative Zn-sensitive broad-spectrum inhibitors of MBLs, specifically imipenemase-1 (IMP-1) from the IBScreen database. Three ligands, STOCK3S-30154, STOCK3S-30418 and STOCK3S-30514 selectively displayed stronger binding interactions with the enzymes compared to reference inhibitors, imipenem and meropenem. For instance, the ligands showed molecular docking scores of -9.450, -8.005 and -10.159 kcal/mol, and MM-GBSA values of -40.404, -31.902 and -33.680 kcal/mol respectively against the IMP-1. Whereas, imipenem and meropenem showed docking scores of -9.038 and -10.875 kcal/mol, and MM-GBSA of -31.184 and -32.330 kcal/mol respectively against the enzyme. The ligands demonstrated good thermodynamic stability and compactness in complexes with IMP-1 throughout the 100 ns molecular dynamics (MD) trajectories. Interestingly, their binding affinities and stabilities were significantly affected in contacts with the remodelled Zn-deficient IMP-1, indicating sensitivity to the carbapenemase active Zn site, however, with non-β-lactam scaffolds, tenable to resist catalytic hydrolysis. They displayed ideal drug-like ADMET properties, thus, representing putative Zn-sensitive non-β-lactam inhibitors of IMP-1 amenable for further experimental studies.

Glial Sphingosine-Mediated Epigenetic Regulation Stabilizes Synaptic Function in Drosophila Models of Alzheimer's Disease

Destabilization of neural activity caused by failures of homeostatic regulation has been hypothesized to drive the progression of Alzheimer's Disease (AD). However, the underpinning mechanisms that connect synaptic homeostasis and the disease etiology are yet to be fully understood. Here, we demonstrated that neuronal overexpression of amyloid β (Aβ) causes abnormal histone acetylation in peripheral glia and completely blocks presynaptic homeostatic potentiation (PHP) at the neuromuscular junction in Drosophila The synaptic deficits caused by Aβ overexpression in motoneurons are associated with motor function impairment at the adult stage. Moreover, we found that a sphingosine analog drug, Fingolimod, ameliorates synaptic homeostatic plasticity impairment, abnormal glial histone acetylation, and motor behavior defects in the Aβ models. We further demonstrated that perineurial glial sphingosine kinase 2 (Sk2) is not only required for PHP, but also plays a beneficial role in modulating PHP in the Aβ models. Glial overexpression of Sk2 rescues PHP, glial histone acetylation, and motor function deficits that are associated with Aβ in Drosophila Finally, we showed that glial overexpression of Sk2 restores PHP and glial histone acetylation in a genetic loss-of-function mutant of the Spt-Ada-Gcn5 Acetyltransferase complex, strongly suggesting that Sk2 modulates PHP through epigenetic regulation. Both male and female animals were used in the experiments and analyses in this study. Collectively, we provided genetic evidence demonstrating that abnormal glial epigenetic alterations in Aβ models in Drosophila are associated with the impairment of PHP and that the sphingosine signaling pathway displays protective activities in stabilizing synaptic physiology.SIGNIFICANCE STATEMENT Fingolimod, an oral drug to treat multiple sclerosis, is phosphorylated by sphingosine kinases to generate its active form. It is known that Fingolimod enhances the cognitive function in mouse models of Alzheimer's disease (AD), but the role of sphingosine kinases in AD is not clear. We bridge this knowledge gap by demonstrating the relationship between impaired homeostatic plasticity and AD. We show that sphingosine kinase 2 (Sk2) in glial cells is necessary for homeostatic plasticity and that glial Sk2-mediated epigenetic signaling has a protective role in synapse stabilization. Our findings demonstrate the potential of the glial sphingosine signaling as a key player in glia-neuron interactions during homeostatic plasticity, suggesting it could be a promising target for sustaining synaptic function in AD.

Unlocking potential inhibitors for Bruton's tyrosine kinase through in-silico drug repurposing strategies

Bruton's tyrosine kinase (BTK) is a non-receptor protein kinase that plays a crucial role in various biological processes, including immune system function and cancer development. Therefore, inhibition of BTK has been proposed as a therapeutic strategy for various complex diseases. In this study, we aimed to identify potential inhibitors of BTK by using a drug repurposing approach. To identify potential inhibitors, we performed a molecular docking-based virtual screening using a library of repurposed drugs from DrugBank. We then used various filtrations followed by molecular dynamics (MD) simulations, principal component analysis (PCA), and Molecular Mechanics Poisson Boltzmann Surface Area (MM-PBSA) analysis to further evaluate the binding interactions and stability of the top-ranking compounds. Molecular docking-based virtual screening approach identified several repurposed drugs as potential BTK inhibitors, including Eltrombopag and Alectinib, which have already been approved for human use. All-atom MD simulations provided insights into the binding interactions and stability of the identified compounds, which will be helpful for further experimental validation and optimization. Overall, our study demonstrates that drug repurposing is a promising approach to identify potential inhibitors of BTK and highlights the importance of computational methods in drug discovery.

HLA3DB: comprehensive annotation of peptide/HLA complexes enables blind structure prediction of T cell epitopes

The class I proteins of the major histocompatibility complex (MHC-I) display epitopic peptides derived from endogenous proteins on the cell surface for immune surveillance. Accurate modeling of peptides bound to the human MHC, HLA, has been mired by conformational diversity of the central peptide residues, which are critical for recognition by T cell receptors. Here, analysis of X-ray crystal structures within our curated database (HLA3DB) shows that pHLA complexes encompassing multiple HLA allotypes present a discrete set of peptide backbone conformations. Leveraging these backbones, we employ a regression model trained on terms of a physically relevant energy function to develop a comparative modeling approach for nonamer pHLA structures named RepPred. Our method outperforms the top pHLA modeling approach by up to 19% in structural accuracy, and consistently predicts blind targets not included in our training set. Insights from our work may be applied towards predicting antigen immunogenicity, and receptor cross-reactivity.

Evolutionary conservation of an ancient retroviral gagpol gene in Artiodactyla

The genomes of mammals contain fingerprints of past infections by ancient retroviruses that invaded the germline of their ancestors. Most of these endogenous retroviruses (ERVs) contain only remnants of the original retrovirus; however, on rare occasions, ERV genes can be co-opted for a beneficial host function. While most studies of co-opted ERVs have focused on envelope genes, including the syncytins that function in placentation, there are examples of co-opted gag genes including one we recently discovered in simian primates. Here, we searched for other intact gag genes in non-primate mammalian lineages. We began by examining the genomes of extant camel species, which represent a basal lineage in the order Artiodactyla. This identified a gagpol gene with a large open reading frame (ORF) (>3,500 bp) in the same orthologous location in Artiodactyla species but that is absent in other mammals. Thus, this ERV was fixed in the common ancestor of all Artiodactyla at least 64 million years ago. The amino acid sequence of this gene, termed ARTgagpol, contains recognizable matrix, capsid, nucleocapsid, and reverse transcriptase domains in ruminants, with an RNase H domain in camels and pigs. Phylogenetic analysis and structural prediction of its reverse transcriptase and RNase H domains groups ARTgagpol with gammaretroviruses. Transcriptomic analysis shows ARTgagpol expression in multiple tissues suggestive of a co-opted host function. These findings identify the oldest and largest ERV-derived gagpol gene with an intact ORF in mammals, an intriguing milestone in the co-evolution of mammals and retroviruses. IMPORTANCE Retroviruses are unique among viruses that infect animals as they integrate their reverse-transcribed double-stranded DNA into host chromosomes. When this happens in a germline cell, such as sperm, egg, or their precursors, the integrated retroviral copies can be passed on to the next generation as endogenous retroviruses (ERVs). On rare occasions, the genes of these ERVs can be domesticated by the host. In this study we used computational similarity searches to identify an ancient ERV with an intact viral gagpol gene in the genomes of camels that is also found in the same genomic location in other even-toed ungulates suggesting that it is at least 64 million years old. Broad tissue expression and predicted preservation of the reverse transcriptase fold of this protein suggest that it may be domesticated for a host function. This is the oldest known intact gagpol gene of an ancient retrovirus in mammals.

Potent multi-target natural inhibitors against SARS-CoV-2 from medicinal plants of the Himalaya: a discovery from hybrid machine learning, chemoinformatics, and simulation assisted screening

The emergence and immune evasion ability of SARS-CoV-2 Omicron strains, mainly BA.5.2 and BF.7 and other variants of concern have raised global apprehensions. With this context, the discovery of multitarget inhibitors may be proven more comprehensive paradigm than its one-drug-to-one target counterpart. In the current study, a library of 271 phytochemicals from 25 medicinal plants from the Indian Himalayan Region has been virtually screened against SARS-CoV-2 by targeting nine virus proteins, viz., papain-like protease, main protease, nsp12, helicase, nsp14, nsp15, nsp16, envelope, and nucleocapsid for screening of a multi-target inhibitor against the viral replication. Initially, 94 phytochemicals were screened by a hybrid machine learning model constructed by combining 6 confirmatory bioassays against SARS-CoV-2 replication using an instance-based learner lazy k-nearest neighbour classifier. Further, 25 screened compounds with excellent drug-like properties were subjected to molecular docking. The phytochemical Cepharadione A from the plant Piper longum showed binding potential against four proteins with the highest binding energy of -10.90 kcal/mol. The compound has acceptable absorption, distribution, metabolism, excretion, and toxicity properties and exhibits stable binding behaviour in terms of root mean square deviation (0.068 ± 0.05 nm), root-mean-square fluctuation, hydrogen bonds, solvent accessible surface area (83.88-161.89 nm2), and molecular mechanics Poisson-Boltzmann surface area during molecular dynamics simulation of 200 ns with selected target proteins. Concerning the utility of natural compounds in the therapeutics formulation, Cepharadione A could be further investigated as a remarkable lead candidate for the development of therapeutic drugs against SARS-CoV-2.Communicated by Ramaswamy H. Sarma.

Assessment of antidiabetic activity of three Phenylspirodrimanes from fungus Stachybotrys chartarum MUT 3308 by ADME, QSAR, molecular docking and molecular dynamics simulation studies against protein tyrosine phosphatase 1B (PTP1B)

Phenylspirodrimanes (PSD) are the sesquiterpene quinone type meroterpenoids found in nature. PSDs are found to exhibit inhibitory activity against immunocomplex diseases, and tyrosine kinase receptors. Three of the different PSDs C1, C2, and C3 that have been reported to be isolated from the sponge-associated fungus Stachybotrys chartarum MUT 3308 are selected for studying their possible inhibitory effect against type 2 diabetes mellitus. Mechanistically, blocking protein tyrosine phosphatase 1B (PTP1B) helps to reduce the insulin resistance induction caused by the high expression of PTP1B. The QSAR, ADME, toxicity (T) study was carried out to predict the pharmacokinetic properties and the biological activities of the PSDs. PASS prediction web tool was used to find and select the target proteins 1NNY, and 2HNP. According to the molecular docking simulations, C1 and C2 showed better binding affinity of -8.5 kcal/mol, and -8.1 kcal/mol respectively against 1NNY compared to the control ligand. RMSD, RMSF, Rg, and SASA analysis revealed that both C1, and C2 showed better stability, minor conformational changes, and minor fluctuation upon binding to PTP1B. Protein contact analysis was carried out to validate the residues that are in contact with the ligands according to molecular docking studies. Overall, C1, and C2 could be proposed as novel natural hits to be developed and small modifications of these PSDs could result in inducing the binding affinity significantly, although experimental validation is required for further evaluation of the work.Communicated by Ramaswamy H. Sarma.

Fisetin induces apoptosis in human skin cancer cells through downregulating MTH1

Fisetin, a natural flavonoid molecule, has been shown to have anticancer properties against various malignancies. In this investigation, we discovered that Fisetin decreased cell viability of both the treated skin cancer cell lines A375 and A431 in a dose and time-dependent manner. The IC50 values ranging from 57.60 µM ± 6.59 to 41.70 µM ± 1.25 in A375 and 48.70 µM ± 5.49 to 33.67 µM ± 1.03 for A431 at the observed time ranging between 24 h to 72 h of treatment remained quite enthusiastic when compared with the normal HEK 293 cells. Fisetin significantly decreased colony formation and migratory ability of the cancer cells. Flow cytometry analysis revealed that Fisetin significantly restricted the progression of skin cancer cells in the G0/G1 phase of the cell cycle and induced cells to undergo apoptosis by increasing reactive oxygen species, decreasing mitochondrial membrane potential, and elevating the count of early and late apoptotic cells. Our in silico studies of molecular docking followed by molecular dynamics simulation found that the interactions and stability of MTH1 protein with Fisetin further showed a considerable binding affinity for MTH1 (-11.4 kcal/mol) and developed stable complexes maintained throughout 100 ns trajectories. Our western blot analysis endorsed this. We found that Fisetin downregulated the expression levels of MTH1 also in addition, it played a crucial role in regulation of apoptotic events in cancer cells. We therefore, conclude that Fisetin anticancer properties against skin cancer cells are mediated through MTH1 inhibition followed by ATM and P53 upregulation.Communicated by Ramaswamy H. Sarma.

Enhanced binding at fever temperatures of HER2 in complex with trastuzumab and pertuzumab

Aim: Fever follows the administration of trastuzumab and pertuzumab used in HER2-relevant immunotherapy, but is often eliminated in clinical practice. This work explores the role of temperature (37-39°C) in the formation of immune complexes between HER2 with either trastuzumab or pertuzumab or with both antibodies. Materials & methods: Using molecular dynamics simulations and free energy calculations, the binding between HER2 and these immunotherapeutic monoclonal antibodies was investigated at different temperatures. Results: Trastuzumab and pertuzumab present the highest binding free energy to HER2 at febrile temperatures (39°C), or when HER2 is in complex with both antibodies. Conclusion: Performing molecular dynamics simulations under fever temperatures may be important for delineating their role in enhancing the binding affinity of mature antibodies used in immunotherapy.