Can correct protein models be identified?

Mutations in LIFR rewire the JAK/STAT signaling pathway: A study unveiling mechanistic details of Stüve-Wiedemann syndrome

Stüve-Wiedemann syndrome (SWS), a rare autosomal recessive disorder, characterized by diminutive size, curvature of the elongated bones, bent fingers, episodes of heightened body temperature, respiratory distress or periods of breath-holding, and challenges with feeding, especially causes fatality in infants. SWS is an outcome of potential missense mutations in the leukemia inhibitory factor receptor gene reflected as numerous amino acid mutations at protein level. Employing in silico tools and techniques like mutational screening with Pred_MutHTP, I-Mutant2.0, PANTHER.db, PolyPhen, to classify mutations as deleterious/destabilizing, in conjunction with experimental data analysis, P136A and S279P emerged as 'effect'-causing mutations. Pre-existing knowledge suggests, SWS progression is effectuated conformationally altered and dysfunctional LIFR, unable to bind to LIF and further form the LIF/LIFR/gp130 signalling complex. To gain functional insights into the effect of the said mutations on the wild type protein, an all-atom, explicit, solvent molecular dynamics simulation was performed following docking approaches. Consequently, referring to the RMSD, RMSF, protein dynamic network analysis, energy landscape plots and domain motion analysis, it was revealed that unbound LIFR_WT was more prone to LIF binding as usual whereas the mutants exhibited considerable domain closure to inhibit LIF binding. We conducted binding affinity analysis via MM/GBSA and dissociation constant estimation after LIFR-LIF docking and found the WT_complex to be more stable and compact as a whole when compared to the flexible mutant complexes thus being associated with SWS. Our study offers a route for understanding molecular level implications upon LIFR mutations which opens an avenue for therapeutic interventions.

Classical molecular dynamics simulation identifies catechingallate as a promising antiviral polyphenol against MPOX palmitoylated surface protein

Cumulative global prevalence of the emergent monkeypox (MPX) infection in the non-endemic countries has been professed as a global public health predicament. Lack of effective MPX-specific treatments sets the baseline for designing the current study. This research work uncovers the effective use of known antiviral polyphenols against MPX viral infection, and recognises their mode of interaction with the target F13 protein, that plays crucial role in formation of enveloped virions. Herein, we have employed state-of-the-art machine learning based AlphaFold2 to predict the three-dimensional structure of F13 followed by molecular docking and all-atoms molecular dynamics (MD) simulations to investigate the differential mode of F13-polyphenol interactions. Our extensive computational approach identifies six potent polyphenols Rutin, Epicatechingallate, Catechingallate, Quercitrin, Isoquecitrin and Hyperoside exhibiting higher binding affinity towards F13, buried inside a positively charged binding groove. Intermolecular contact analysis of the docked and MD simulated complexes divulges three important residues Asp134, Ser137 and Ser321 that are observed to be involved in ligand binding through hydrogen bonds. Our findings suggest that ligand binding induces minor conformational changes in F13 to affect the conformation of the binding site. Concomitantly, essential dynamics of the six-MD simulated complexes reveals Catechin gallate, a known antiviral agent as a promising polyphenol targeting F13 protein, dominated with a dense network of hydrophobic contacts. However, assessment of biological activities of these polyphenols need to be confirmed through in vitro and in vivo assays, which may pave the way for development of new novel antiviral drugs.

Exploring the structural assembly of rice ADP-glucose pyrophosphorylase subunits using MD simulation

ADP-glucose pyrophosphorylase plays a pivotal role as an allosteric enzyme, essential for starch biosynthesis in plants. The higher plant AGPase comparises of a pair of large and a pair of small subunits to form a heterotetrameric complex. Growing evidence indicates that each subunit plays a distinct role in regulating the underlying mechanism of starch biosynthesis. In the rice genome, there are four large subunit genes (OsL1-L4) and three small subunit genes (OsS1, OsS2a, and OsS2b). While the structural assembly of cytosolic rice AGPase subunits (OsL2:OsS2b) has been elucidated, there is currently no such documented research available for plastidial rice AGPases (OsL1:OsS1). In this study, we employed protein modeling and MD simulation approaches to gain insights into the structural association of plastidial rice AGPase subunits. Our results demonstrate that the heterotetrameric association of OsL1:OsS1 is very similar to that of cytosolic OsL2:OsS2b and potato AGPase heterotetramer (StLS:StSS). Moreover, the yeast-two-hybrid results on OsL1:OsS1, which resemble StLS:StSS, suggest a differential protein assembly for OsL2:OsS2b. Thus, the regulatory and catalytic mechanisms for plastidial AGPases (OsL1:OsS1) could be different in rice culm and developing endosperm compared to those of OsL2:OsS2b, which are predominantly found in rice endosperm.

Atom-ProteinQA: Atom-level protein model quality assessment through fine-grained joint learning

MOTIVATION

Protein model quality assessment (ProteinQA) is a fundamental task that is essential for biologically relevant applications, i.e., protein structure refinement, protein design, etc. Previous works aimed to conduct ProteinQA only on the global structure or per-residue level, ignoring potentially usable and precise cues from a fine-grained per-atom perspective. In this study, we propose an atom-level ProteinQA model, named Atom-ProteinQA, in which two innovative modules are designed to extract geometric and topological atom-level relationships respectively. Specifically, on the one hand, a geometric perception module exploits 3D sparse convolution to capture the geometric features of the input protein, generating fine-grained atom-level predictions. On the other hand, natural chemical bonds are utilized to construct an atom-level graph, then message passing from a topological perception module is applied to output residue-level predictions in parallel. Eventually, through a cross-model aggregation module, features from different modules mutually interact, enhancing performance on both the atom and residue levels.

RESULTS

Extensive experiments show that our proposed Atom-ProteinQA outperforms previous methods by a large margin, regardless of residue-level or atom-level assessment. Concretely, we achieved state-of-the-art performance on CATH-2084, Decoy-8000, public benchmarks CASP13 & CASP14, and the CAMEO.

AVAILABILITY

The repository of this project is released on: https://github.com/luyfcandy/Atom_ProteinQA.

Structural insights of Labeo catla (catla) myxovirus resistance protein,GTP binding recognition and constitutive expression induced with Poly I:C

The Myxovirus resistance (Mx) proteins are critical effectors belonging to the super-family of guanidine triphosphatase, often stimulated by type I interferon (IFN) and mediates antiviral responses to restrict the replication of numerous viral genes in fishes. In teleosts, Mx proteins display diverse and complicated antiviral activity in different species. The present investigation seeks to characterize the Mx gene from Labeo catla upon induction by double-stranded (ds) RNA, polyinosinic-polycytidylic acid, (poly I: C). Molecular modeling and all-atoms molecular dynamics (MD) simulations were employed to understand the architecture of the GTPase domain and its plausible mode of GTP recognition in Mx protein. The full-length L. catla Mx (LcMx) gene sequence (1821 bp nucleotides) encodes an open reading frame of 606 amino acids. Domain search indicated conserved tripartite domain architecture of LcMx and forms a major cluster with the Mx from other teleosts. The positively charged Arginine and polar Glutamine residues from helix 3 and 4 of stalk region LcMx aid in homo-oligomerization. MD simulation portrayed the role of conserved critical residues aid in GTP recognition by the GTPase domain which perfectly corroborates with experimental findings and prior MD studies. After injection of poly I:C, the temporal mRNA profile showed that LcMx expression was significantly elevated in the spleen, brain, kidney, liver, muscle, heart, intestine, and gill tissues. Collectively, these results suggest that the elevated expression of the major innate immune defense gene Mx was able to inhibit the poly I: C mediated virulence in fish.Communicated by Ramaswamy H. Sarma.

Immunoinformatic based designing of potential immunogenic novel mRNA and peptide-based prophylactic vaccines against H5N1 and H7N9 avian influenza viruses

Influenza viruses are the most common cause of serious respiratory illnesses worldwide and are responsible for a significant number of annual fatalities. Therefore, it is crucial to look for new immunogenic sites that might trigger an effective immune response. In the present study, bioinformatics tools were used to design mRNA and multiepitope-based vaccines against H5N1 and H7N9 subtypes of avian influenza viruses. Several Immunoinformatic tools were employed to extrapolate T and B lymphocyte epitopes of HA and NA proteins of both subtypes. The molecular docking approach was used to dock the selected HTL and CTL epitopes with the corresponding MHC molecules. Eight (8) CTL, four (4) HTL, and Six (6) linear B cell epitopes were chosen for the structural arrangement of mRNA and of peptide-based prophylactic vaccine designs. Different physicochemical characteristics of the selected epitopes fitted with suitable linkers were analyzed. High antigenic, non-toxic, and non-allergenic features of the designed vaccines were noted at a neutral physiological pH. Codon optimization tool was used to check the GC content and CAI value of constructed MEVC-Flu vaccine, which were recorded to be 50.42% and 0.97 respectively. the GC content and CAI value verify the stable expression of vaccine in pET28a + vector. In-silico immunological simulation the MEVC-Flu vaccine construct revealed a high level of immune responses. The molecular dynamics simulation and docking results confirmed the stable interaction of TLR-8 and MEVC-Flu vaccine. Based on these parameters, vaccine constructs can be regarded as an optimistic choice against H5N1 and H7N9 strains of the influenza virus. Further experimental testing of these prophylactic vaccine designs against pathogenic avian influenza strains may clarify their safety and efficacy.Communicated by Ramaswamy H. Sarma.

In silico approaches for the identification of potential allergens among hypothetical proteins from Alternaria alternata and its functional annotation

Direct exposure to the fungal species Alternaria alternata is a major risk factor for the development of asthma, allergic rhinitis, and inflammation. As of November 23rd 2020, the NCBI protein database showed 11,227 proteins from A. alternata genome as hypothetical proteins (HPs). Allergens are the main causative of several life-threatening diseases, especially in fungal infections. Therefore, the main aim of the study is to identify the potentially allergenic inducible proteins from the HPs in A. alternata and their associated functional assignment for the complete understanding of the complex biological systems at the molecular level. AlgPred and Structural Database of Allergenic Proteins (SDAP) were used for the prediction of potential allergens from the HPs of A. alternata. While analyzing the proteome data, 29 potential allergens were predicted by AlgPred and further screening in SDAP confirmed the allergic response of 10 proteins. Extensive bioinformatics tools including protein family classification, sequence-function relationship, protein motif discovery, pathway interactions, and intrinsic features from the amino acid sequence were used to successfully predict the probable functions of the 10 HPs. The functions of the HPs are characterized as chitin-binding, ribosomal protein P1, thaumatin, glycosyl hydrolase, and NOB1 proteins. The subcellular localization and signal peptide prediction of these 10 proteins has further provided additional information on localization and function. The allergens prediction and functional annotation of the 10 proteins may facilitate a better understanding of the allergenic mechanism of A. alternata in asthma and other diseases. The functional domain level insights and predicted structural features of the allergenic proteins help to understand the pathogenesis and host immune tolerance. The outcomes of the study would aid in the development of specific drugs to combat A. alternata infections.

Escherichia coli FtsZ molecular dynamics simulations

Earlier molecular dynamics studies of the FtsZ protein revealed that the protein has high intrinsic flexibility which the crystal structures cannot reveal. However, the input structure in these simulation studies was based on the available crystal structure data and therefore, the effect of the C-terminal Intrinsically Disordered Region (IDR) of FtsZ could not be observed in any of these studies. Recent investigations have revealed that the C-terminal IDR is crucial for FtsZ assembly in vitro and Z ring formation in vivo. Therefore, in this study, we simulated FtsZ with the IDR. Simulations of the FtsZ monomer in different nucleotide bound forms (without nucleotide, GTP, GDP) were performed. In the conformations of FtsZ monomer with GTP, GTP binds variably with the protein. Such a variable interaction with the monomer has not been observed in any previous simulation studies of FtsZ and not observed in crystal structures. We found that central helix bends towards the C-terminal domain in the GTP bound form, hence, making way for polymerization. A nucleotide dependent shift/rotation of the C-terminal domain was observed in simulation time averaged structures.Communicated by Ramaswamy H. Sarma.

SLAM (CD150) receptor homologous peptides block the peste des petits ruminants virus entry into B95a cells

The fusion of haemagglutinin-neuraminidase (HN) protein of peste des petits ruminant (PPR) virus with signaling lymphocyte activation molecules (SLAM) host cell receptor consequences the virus entry and multiplication inside the host cell. The use of synthetic SLAM homologous peptides (i.e., molecular decoy for HN protein of PPR virus) may check PPR infection at the preliminary stage. Hence, the predicted SLAM homologous peptides using bioinformatics tools were synthesized by solid phase chemistry with standard Merrifield's 9-fluorenylmethoxycarbonyl (Fmoc) chemistry and were purified by reverse phase high performance liquid chromatography. The secondary structures of synthesized peptides were elucidated by circular dichroism spectroscopy. The in vitro interactions of these peptides were studied through indirect Enzyme Linked Immuno Sorbent Assay (ELISA) and visual surface plasmon UV-visible spectroscopy. The SLAM homologous peptides were able to interact with the peste des petits ruminant virus (PPRV) with varying binding efficiency. The interaction of SLAM homologous peptide with the PPR virus was ascertained by the change in the plasmon color from red wine to purple during visual detection and also by bathochromic shift in absorbance spectra under UV-visible spectrophotometry. The cytotoxic and anti-PPRV effect of these peptides were also evaluated in B95a cell line using PPR virus (Sungri/96). The cytotoxic concentration 50 (CC50 ) value of each peptide was greater than 1000 μg mL-1 . The anti-PPRV efficiency of SLAM-22 was relatively high among SLAM homologous peptides, SLAM-22 at 25 μg mL-1 concentration showed a reduction of more than log10 3 virus titer by priming of B95a cell line while the use of SLAM-15 and Muco-17 at the same concentration dropped virus titer from log10 4.8 to log10 2.5 and log10 3.1 respectively. The concentration of SLAM homologous peptide (25 μg mL-1 ) to exert its anti-PPRV effect was much less than its CC50 level (>1000 μg mL-1 ). Therefore, the synthetic SLAM homologous peptides may prove to be better agents to target PPRV.

Protein structure accuracy estimation using geometry-complete perceptron networks

Estimating the accuracy of protein structural models is a critical task in protein bioinformatics. The need for robust methods in the estimation of protein model accuracy (EMA) is prevalent in the field of protein structure prediction, where computationally-predicted structures need to be screened rapidly for the reliability of the positions predicted for each of their amino acid residues and their overall quality. Current methods proposed for EMA are either coupled tightly to existing protein structure prediction methods or evaluate protein structures without sufficiently leveraging the rich, geometric information available in such structures to guide accuracy estimation. In this work, we propose a geometric message passing neural network referred to as the geometry-complete perceptron network for protein structure EMA (GCPNet-EMA), where we demonstrate through rigorous computational benchmarks that GCPNet-EMA's accuracy estimations are 47% faster and more than 10% (6%) more correlated with ground-truth measures of per-residue (per-target) structural accuracy compared to baseline state-of-the-art methods for tertiary (multimer) structure EMA including AlphaFold 2. The source code and data for GCPNet-EMA are available on GitHub, and a public web server implementation is freely available.

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

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

Developing Lipase Inhibitor as a Novel Approach to Address the Rice Bran Rancidity Issue─A Critical Review

Rice bran is a valuable byproduct from the food processing industry, which contains abundant protein, essential unsaturated fatty acids, and numerous bioactive compounds. However, its susceptibility to rancidity greatly restricts its wide utilization. Many strategies have been proposed to delay the rancidity of rice bran, but most of them have their respective limitations. Here, we proposed that developing rice ban lipase peptide inhibitors represents an alternative and promising prescription for impeding the rancidity of rice bran, in contrast to the conventional stabilization approaches for rice bran. For this reason, the rancidity mechanisms of rice bran and the research progress of rice bran lipases were discussed. In addition, the feasibility of utilizing in silico screening and phage display, two state-of-the-art technologies, in the design of the related peptide inhibitors was also highlighted. This knowledge is expected to provide a theoretical basis for opening a new avenue for stabilizing rice bran.

Potential inhibitors of RPS6KB2 and NRF2 in head and neck squamous cell carcinoma

Among the major altered pathways in head and neck squamous cell carcinoma, AKT/mTORC1/S6K and NRF2/KEAP1 pathway are quite significant. The overexpression and overstimulation of proteins from both these pathways makes them the promising candidates in cancer therapeutics. Inhibiting mTOR has been in research from past several decades but the tumour heterogeneity, and upregulation of several compensatory feed-back mechanisms, encourages to explore other downstream targets for inhibiting the pathway. One such downstream effectors of mTOR is S6K2. It is reported to be overexpressed in cancers such as head and neck cancer, breast cancer and prostate cancer. In case of NRF2/KEAP1 pathway, nuclear factor erythroid 2-related factor 2 (NFE2L2 or NRF2) is overexpressed in ∼90% of head and neck squamous cell carcinoma (HNSCC) cases. It associates with poor survival rate and therapeutic resistance in HNSCC treatment. NRF2 pathway is the primary antioxidant pathway in the cell which also serves pro-tumorigenic functions, such as repression of apoptosis, cell proliferation support and chemoresistance. The aim of this work was to explore S6K2 and NRF2 and identify novel and potential inhibitors against them for treating head and neck squamous cell carcinoma. Since the crystal structure of S6K2 was not available at the time of this study, we modelled its structure using homology modelling and performed high throughput screening, molecular dynamics simulations, free energy calculations and protein-ligand interaction studies to identify the inhibitors. We identified natural compounds Crocin and Gypenoside XVII against S6K2 and Chebulinic acid and Sennoside A against NRF2. This study provides a significant in-depth understanding of the two studied pathways and therefore can be used in the development of potential therapeutics against HNSCC.Communicated by Ramaswamy H. Sarma.

Enhancing the activity of β-lactamase inhibitory protein-II with cell-penetrating peptide against KPC-2-carrying Klebsiella pneumoniae

Carbapenem-resistant Enterobacterales (CRE) is considered a paramount threat due to its rapid spread and high mortality rate. Klebsiella pneumoniae carbapenemases (KPCs), specifically KPC-2, are prevalent enzymes responsible for carbapenem resistance in many countries. While combinations of antibiotics are commonly used, they must be tailored to match the remaining susceptibility of the infecting strains. Therefore, there is a need to develop the β-lactamase inhibitor to effectively address this issue. β-lactamase inhibitor protein (BLIP) and its variants, BLIP-I and BLIP-II, have demonstrated the ability to inhibit class A β-lactamases. In particular, BLIP-II shows strong binding to the KPC-2 carbapenemase, making it a potential candidate for inhibition. To improve the intracellular penetration of BLIP-II, a cell-penetrating peptide (CPP) was employed. In this study, a KRK-rich peptide was introduced at either the N-terminal or C-terminal region of tBLIP-II, excluding the signal sequence of the BLIP-II protein. tBLIP-II, tBLIP-II-CPP, and CPP-BLIP-II were successfully expressed, and the chimeric proteins retained inhibitory activity compared to tBLIP-II alone. It is apparent that homology modeling demonstrated neither the poly-histidine tag nor the CPP interfered with the essential interaction residues of tBLIP-II. Interestingly, BLIP-II-CPP exhibited the highest inhibitory activity, reducing the minimal inhibitory concentration (MIC) of meropenem by 8 folds. Moreover, the combination of tBLIP-CPP with meropenem significantly decreased the viable bacterial cell count compared to the combination of tBLIP-II with meropenem or meropenem alone. These findings suggest that tBLIP-CPP is a promising candidate for restoring carbapenem susceptibility against CRE and provides a valuable therapeutic option for infections caused by CRE.

Molecular docking and dynamics simulation studies uncover the host-pathogen protein-protein interactions in Penaeus vannamei and Vibrio parahaemolyticus

Shrimp aquaculture contributes significantly to global economic growth, and the whiteleg shrimp, Penaeus vannamei, is a leading species in this industry. However, Vibrio parahaemolyticus infection poses a major challenge in ensuring the success of P. vannamei aquaculture. Despite its significance in this industry, the biological knowledge of its pathogenesis remains unclear. Hence, this study was conducted to identify the interaction sites and binding affinity between several immune-related proteins of P. vannamei with V. parahaemolyticus proteins associated with virulence factors. Potential interaction sites and the binding affinity between host and pathogen proteins were identified using molecular docking and dynamics (MD) simulation. The P. vannamei-V. parahaemolyticus protein-protein interaction of Complex 1 (Ferritin-HrpE/YscL family type III secretion apparatus protein), Complex 2 (Protein kinase domain-containing protein-Chemotaxis CheY protein), and Complex 3 (GPCR-Chemotaxis CheY protein) was found to interact with -4319.76, -5271.39, and -4725.57 of the docked score and the formation of intermolecular bonds at several interacting residues. The docked scores of Complex 1, Complex 2, and Complex 3 were validated using MD simulation analysis, which revealed these complexes greatly contribute to the interactions between P. vannamei and V. parahaemolyticus proteins, with binding free energies of -22.50 kJ/mol, -30.20 kJ/mol, and -26.27 kJ/mol, respectively. This finding illustrates the capability of computational approaches to search for molecular binding sites between host and pathogen, which could increase the knowledge of Vibrio spp. infection on shrimps, which then can be used to assist in the development of effective treatment.

Elucidation of the structural dynamics of mutations in PHB2 protein associated with growth suppression and cancer progression

Prohibitin is a multifunctional protein that plays an important role in numerous cellular processes. Membrane-associated mitochondrial prohibitin complex is made up of two subunits, PHB1 and PHB2 which are ubiquitously expressed and analogous to each other. High levels of prohibitin expression have consequently been found in esophageal cancer, endometrial adenocarcinoma, gastric cancer, hepatocellular carcinoma, breast cancer and bladder cancer. The aim of this study is to analyse two-point mutation PHB2_MT1(I → A) and PHB2_MT2(I → P), their effect on PHB2 protein and its effect on formation of mitochondrial complex. It is a residual level study, based on current experimental validation. To establish the effects of the two-point mutations, computational approaches such as molecular modelling, molecular docking, normal mode simulation, molecular dynamics simulations and MM/GBSA were used. An analysis of the energy dynamics of both unbound and complex proteins was conducted to elucidate how mutations impact the energy distribution of PHB2. Our study confirmed that the two mutations decreased the overall stability of PHB2. This was evidenced by heightened atomic fluctuations within the mutated region, accompanied by elevated deviations observed in RMSD and Rg values. Furthermore, these mutations were correlated with a decline in the organization of secondary structural elements. The mutations in PHB2_MT1 and PHB2_MT2 resulted in formation a less stable prohibitin complex. Thus, PHB1 and PHB2 may act as molecular target or novel biomarkers for therapeutic intervention in numerous forms of malignancies.

Comparative analysis of SilA-laccase mediated degradation of ciprofloxacin, norfloxacin and ofloxacin and interpretation of the possible catalytic mechanism

Fluoroquinolones (FQs) are the most commonly used antimicrobial drugs and regardless of their advantages in the healthcare sector, the pollution of these antimicrobial drugs in the environment has big concerns about human and environmental health. The presence of these antibiotic drugs even at the lowest concentrations in the environment has resulted in the emergence and spread of antibiotic resistance. Hence, it is necessary to remediate these pollutants from the environment. Previously alkaline laccase (SilA) from Streptomyces ipomoeae has been demonstrated to show degrading potentials against two of the FQs, Ciprofloxacin (CIP) and Norfloxacin (NOR); however, the molecular mechanism was not elucidated in detail. In this study, we have analyzed the possible molecular catalytic mechanism of FQ degrading SilA-laccase for the degradation of the FQs, CIP, NOR and Ofloxacin (OFL) using three-dimensional protein structure modeling, molecular docking and molecular dynamic (MD) studies. The comparative protein sequence analysis revealed the presence of tetrapeptide conserved catalytic motif, His102-X-His104-Gly105. After evaluating the active site of the enzyme in depth using CDD, COACH and S-site tools, we have identified the catalytic triad composed of three conserved amino acid residues, His102, Val103 and Tyr108 with which ligands interacted during the catalysis process. By analyzing the MD trajectories, it is revealed that the highest degradation potential of SilA is for CIP followed by NOR and OFL. Ultimately, this study provides the possible comparative catalytic mechanism for the degradation of CIP, NOR and OFL by the SilA enzyme.Communicated by Ramaswamy H. Sarma.

Identification of allosteric inhibitor against AKT1 through structure-based virtual screening

AKT (serine/threonine protein kinase) is a potential therapeutic target for many types of cancer as it plays a vital role in cancer progression. Many AKT inhibitors are already in practice under single and combinatorial therapy. However, most of these inhibitors are orthosteric / pan-AKT that are non-selective and non-specific to AKT kinase and their isoforms. Hence, researchers are searching for novel allosteric inhibitors that bind in the interface between pH and kinase domain. In this study, we performed structure-based virtual screening from the afroDB (a diverse natural compounds library) to find the potential inhibitor targeting the AKT1. These compounds were filtered through Lipinski, ADMET properties, combined with a molecular docking approach to obtain the 8 best compounds. Then we performed molecular dynamics simulation for apoprotein, AKT1 with 8 complexes, and AKT1 with the positive control (Miransertib). Molecular docking and simulation analysis revealed that Bianthracene III (hit 1), 10-acetonyl Knipholonecyclooxanthrone (hit 2), Abyssinoflavanone VII (hit 5) and 8-c-p-hydroxybenzyldiosmetin (hit 6) had a better binding affinity, stability, and compactness than the reference compound. Notably, hit 1, hit 2 and hit 5 had molecular features required for allosteric inhibition.

Potential inhibitors of FemC to combat Staphylococcus aureus: virtual screening, molecular docking, dynamics simulation, and MM-PBSA analysis

FemC is a methicillin resistance factor involved in the alterations of peptidoglycan and glutamine synthesis in Staphylococcus aureus. To identify the potent antibacterial agents, antibacterial molecules were screened against the predicted and validated FemC model. Based on docking scores, presence of essential interactions with active site residues of FemC, pharmacokinetic, and ADMET properties, six candidates were shortlisted and subjected to molecular dynamics to evaluate the stability of FemC-ligand complexes. Further, per residue decomposition analysis and Molecular Mechanics/Poisson-Boltzmann Surface Area (MMPBSA) analysis confirmed that S15, M16, S17, R31, R43, Q47, K48 and R49 of FemC played a vital role in the formation of lower energy stable FemC-inhibitor(s) complexes. Therefore, in the present study, the reported six molecules (Z317461228, Z92241701, Z30923155, Z30202349, Z2609517102 and Z92470167) may pave the path to design the scaffold of novel potent antimicrobials against S. aureus.Communicated by Ramaswamy H. Sarma.

Protein quality assessment with a loss function designed for high-quality decoys

Motivation: The prediction of a protein 3D structure is essential for understanding protein function, drug discovery, and disease mechanisms; with the advent of methods like AlphaFold that are capable of producing very high-quality decoys, ensuring the quality of those decoys can provide further confidence in the accuracy of their predictions. Results: In this work, we describe Qϵ, a graph convolutional network (GCN) that utilizes a minimal set of atom and residue features as inputs to predict the global distance test total score (GDTTS) and local distance difference test (lDDT) score of a decoy. To improve the model's performance, we introduce a novel loss function based on the ϵ-insensitive loss function used for SVM regression. This loss function is specifically designed for evaluating the characteristics of the quality assessment problem and provides predictions with improved accuracy over standard loss functions used for this task. Despite using only a minimal set of features, it matches the performance of recent state-of-the-art methods like DeepUMQA. Availability: The code for Qϵ is available at https://github.com/soumyadip1997/qepsilon.

Extensive characterization of 28 complete chloroplast genomes of Hydrangea species: A perspective view of their organization and phylogenetic and evolutionary relationships

The tribe Hydrangeeae displays a unique, distinctive disjunct distribution encompassing East Asia, North America and Hawaii. Despite its complex trait variations and polyphyletic nature, comprehensive phylogenomic and biogeographical studies on this tribe have been lacking. To address this gap, we sequenced and characterized 28 plastomes of Hydrangeeae. Our study highlights the highly conserved nature of Hydrangeaceae chloroplast (cp) genomes in terms of gene content and arrangement. Notably, synapomorphic characteristics of tandem repeats in the conserved domain of accD were observed in the Macrophyllae, Chinenses, and Dichroa sections within the Hydrangeeae tribe. Additionally, we found lower expression of accD in these sections using structure prediction and quantitative real-time PCR analysis. Phylogenomic analyses revealed the subdivision of the Hydrangeeae tribe into two clades with robust support values. Consistent with polyphyletic relationships, sect. Broussaisia was identified as the basal group in the tribe Hydrangeeae. Our study also provides insights into the phylogenetic relationships of Hydrangea petiolaris in the Jeju and Ulleung Island populations, suggesting the need for further studies with more samples and molecular data. Divergence time estimation and biogeographical analyses suggested that the common ancestors of the tribe Hydrangeeae likely originated from North America and East Asia during the Paleocene period via the Bering Land Bridge, potentially facilitating migration within the tribe between these regions. In conclusion, this study enhances our understanding of the evolutionary history and biogeography of the tribe Hydrangeeae, shedding light on the dispersal patterns and origins of this intriguing plant group with its unique disjunct distribution.

Exploiting the potential of natural polyphenols as antivirals against monkeypox envelope protein F13 using machine learning and all-atoms MD simulations

The re-emergence of monkeypox (MPX), in the era of COVID-19 pandemic is a new global menace. Regardless of its leniency, there are chances of MPX expediting severe health deterioration. The role of envelope protein, F13 as a critical component for production of extracellular viral particles makes it a crucial drug target. Polyphenols, exhibiting antiviral properties have been acclaimed as an effective alternative to the traditional treatment methods for management of viral diseases. To facilitate the development of potent MPX specific therapeutics, herein, we have employed state-of-the-art machine learning techniques to predict a highly accurate 3-dimensional structure of F13 as well as identify binding hotspots on the protein surface. Additionally, we have effectuated high-throughput virtual screening methodology on 57 potent natural polyphenols having antiviral activities followed by all-atoms molecular dynamics (MD) simulations, to substantiate the mode of interaction of F13 protein and polyphenol complexes. The structure-based virtual screening based on Glide SP, XP and MM/GBSA scores enables the selection of six potent polyphenols having higher binding affinity towards F13. Non-bonded contact analysis, of pre- and post- MD complexes propound the critical role of Glu143, Asp134, Asn345, Ser321 and Tyr320 residues in polyphenol recognition, which is well supported by per-residue decomposition analysis. Close-observation of the structural ensembles from MD suggests that the binding groove of F13 is mostly hydrophobic in nature. Taken together, this structure-based analysis from our study provides a lead on Myricetin, and Demethoxycurcumin, which may act as potent inhibitors of F13. In conclusion, our study provides new insights into the molecular recognition and dynamics of F13-polyphenol bound states, offering new promises for development of antivirals to combat monkeypox. However, further in vitro and in vivo experiments are necessary to validate these results.

Structure based virtual screening and molecular dynamics of natural anti-biofilm compounds against SagS response regulator/sensor kinase in Pseudomonas aeruginosa

SagS sensor regulator plays a vital role in biofilm development of Pseudomonas aeruginosa which subsequently makes the cells more tolerant to various antimicrobials. The multidrug resistance (MDR) issue has risen substantially in recent years and is considered a global threat. Therefore, alternative compounds should be unearthed immediately to address the issues related to P. aeruginosa drug resistance for which SagS could be a candidate. The present study is an attempt to screen natural anti-biofilm compounds as the potent inhibitors of SagS. Twenty natural anti-biofilm/quorum sensing inhibiting compounds were retrieved from various literatures with significant inhibitory effects against P. aeruginosa biofilm from in-vitro experiments which were screened using various pharmacokinetic parameters. The screened and three standard drugs were docked against SagS-HisKA using AutoDock 4.2 tool, which were further analysed by MD simulations to understand the binding mode of compounds and dynamic behaviour of the complexes. Two potential anti-biofilm natural compounds, pinocembrin with binding affinity (-7.19 kcal/mol), vestitol (-7.18 kcal/mol) and the standard drug ceftazidime (-8.89 kcal/mol) were selected based on filtered parameters and better binding affinity. The trajectory analysis of MD simulations reflected Pinocembrin in stabilizing the system compared to ceftazidime. The existing reports state that the natural products represent promising source of therapy with least or almost nil adverse effect compared to synthetic drugs which is well collated with our in-silico findings. This investigation can save both time and cost required for in-vitro and in-vivo analysis for designing of a novel anti-biofilm agent against P. aeruginosa biofilm-associated infections.Communicated by Ramaswamy H. Sarma.

iQDeep: an integrated web server for protein scoring using multiscale deep learning models

The remarkable recent advances in protein structure prediction have enabled computational modeling of protein structures with considerably higher accuracy than ever before. While state-of-the-art structure prediction methods provide self-assessment confidence scores of their own predictions, an independent and open-access system for protein scoring is still needed that can be applied to a broad range of predictive modeling scenarios. Here, we present iQDeep, an integrated and highly customizable web server for protein scoring, freely available at http://fusion.cs.vt.edu/iQDeep. The underlying method of iQDeep employs multiscale deep residual neural networks (ResNets) to perform residue-level error classifications, and then probabilistically combines the error classifications for protein scoring. By adjusting the error resolutions, our method can reliably estimate the standard- or high-accuracy variants of the Global Distance Test metric for versatile protein scoring. The performance of the method has been extensively tested and compared against the state-of-the-art approaches in multiple rounds of Critical Assessment of Techniques for Protein Structure Prediction (CASP) experiments including benchmark assessment in CASP12 and CASP13 as well as blind evaluation in CASP14. The iQDeep web server offers a number of convenient features, including (i) the choice of individual and batch processing modes; (ii) an interactive and privacy-preserving web interface for automated job submission, tracking, and results retrieval; (iii) web-based quantitative and visual analyses of the results including overall estimated score and its residue-wise breakdown along with agreements between various sequence- and structural-level features; (iv) extensive help information on job submission and results interpretation via web-based tutorial and help tooltips.

Insights into the binding mechanism of ascorbic acid and violaxanthin with violaxanthin de-epoxidase (VDE) and chlorophycean violaxanthin de-epoxidase (CVDE) enzymes

Photosynthetic organisms have evolved to work under low and high lights in photoprotection, acting as a scavenger of reactive oxygen species. The light-dependent xanthophyll cycle involved in this process is performed by a key enzyme (present in the thylakoid lumen), Violaxanthin De-Epoxidase (VDE), in the presence of violaxanthin (Vio) and ascorbic acid substrates. Phylogenetically, VDE is found to be connected with an ancestral enzyme Chlorophycean Violaxanthin De-Epoxidase (CVDE), present in the green algae on the stromal side of the thylakoid membrane. However, the structure and functions of CVDE were not known. In search of functional similarities involving this cycle, the structure, binding conformation, stability, and interaction mechanism of CVDE are explored with the two substrates compared to VDE. The structure of CVDE was determined by homology modeling and validated. In silico docking (of first-principles optimized substrates) revealed it has a larger catalytic domain than VDE. A thorough analysis of the binding affinity and stability of four enzyme-substrate complexes is performed by computing free energies and their decomposition, the root-mean-square deviation (RMSD) and fluctuation (RMSF), the radius of gyration, salt bridge, and hydrogen bonding interactions in molecular dynamics. Based on these, violaxanthin interacts with CVDE to a similar extent as that of VDE. Hence, its role is expected to be the same for both enzymes. On the contrary, ascorbic acid has a weaker interaction with CVDE than VDE. Given these interactions drive epoxidation or de-epoxidation in the xanthophyll cycle, it immediately discerns that either ascorbic acid does not participate in de-epoxidation or a different cofactor is necessary as CVDE has a weaker interaction with ascorbic acid than VDE.

Discovery of andrographolide hit analog as a potent cyclooxygenase-2 inhibitor through consensus MD-simulation, electrostatic potential energy simulation and ligand efficiency metrics

Cyclooxygenase-2 (COX-2) is the key enzyme responsible for the conversion of arachidonic acid to prostaglandins that display pro-inflammatory properties and thus, it is a potential target protein to develop anti-inflammatory drugs. In this study, chemical and bio-informatics approaches have been employed to find a novel potent andrographolide (AGP) analog as a COX-2 inhibitor having better pharmacological properties than aspirin and rofecoxib (controls). The full amino acid sequenced human Alpha fold (AF) COX-2 protein (604AA) was selected and validated for its accuracy against the reported COX-2 protein structures (PDB ID: 5F19, 5KIR, 5F1A, 5IKQ and 1V0X) followed by multiple sequence alignment analysis to establish the sequence conservation. The systematic virtual screening of 237 AGP analogs against AF-COX-2 protein yielded 22 lead compounds based on the binding energy score (< - 8.0 kcal/mol). These were further screened out to 7 analogs by molecular docking analysis and investigated further for ADMET prediction, ligand efficiency metrics calculations, quantum mechanical analysis, MD simulation, electrostatic potential energy (EPE) docking simulation, and MM/GBSA. In-depth analysis revealed that AGP analog A3 (3-[2-[(1R,4aR,5R,6R,8aR)-6-hydroxy-5,6,8a-trimethyl-2-methylidene-3,4,4a,5,7,8-hexahydro-1H-naphthalen-1-yl]ethylidene]-4-hydroxyoxolan-2-one) forms the most stable complex with the AF-COX-2 showing the least RMSD value (0.37 ± 0.03 nm), a good number of hydrogen bonds (protein-ligand H-bond = 11, and protein H-bond = 525), minimum EPE score (- 53.81 kcal/mol), and lowest MM-GBSA before and after simulation (- 55.37 and - 56.25 kcal/mol, respectively) value compared to other analogs and controls. Thus, we suggest that the identified A3 AGP analog could be developed as a promising plant-based anti-inflammatory drug by inhibiting COX-2.

Chimeric Peptides from Californiconus californicus and Heterodontus francisci with Antigen-Binding Capacity: A Conotoxin Scaffold to Create Non-Natural Antibodies (NoNaBodies)

Research into various proteins capable of blocking metabolic pathways has improved the detection and treatment of multiple pathologies associated with the malfunction and overexpression of different metabolites. However, antigen-binding proteins have limitations. To overcome the disadvantages of the available antigen-binding proteins, the present investigation aims to provide chimeric antigen-binding peptides by binding a complementarity-determining region 3 (CDR3) of variable domains of new antigen receptors (VNARs) with a conotoxin. Six non-natural antibodies (NoNaBodies) were obtained from the complexes of conotoxin cal14.1a with six CDR3s from the VNARs of Heterodontus francisci and two NoNaBodies from the VNARs of other shark species. The peptides cal_P98Y vs. vascular endothelial growth factor 165 (VEGF165), cal_T10 vs. transforming growth factor beta (TGF-β), and cal_CV043 vs. carcinoembryonic antigen (CEA) showed in-silico and in vitro recognition capacity. Likewise, cal_P98Y and cal_CV043 demonstrated the capacity to neutralize the antigens for which they were designed.

Deletion of the ATP20 gene in Ustilago maydis produces an unstable dimer of F1FO-ATP synthase associated with a decrease in mitochondrial ATP synthesis and a high H2O2 production

The F₁F_O-ATP synthase uses the energy stored in the electrochemical proton gradient to synthesize ATP. This complex is found in the inner mitochondrial membrane as a monomer and dimer. The dimer shows higher ATPase activity than the monomer and is essential for cristae folding. The monomer-monomer interface is constituted by subunits a, i/j, e, g, and k. The role of the subunit g in a strict respiratory organism is unknown. A gene knockout was generated in Ustilago maydis to study the role of subunit g on mitochondrial metabolism and cristae architecture. Deletion of the ATP20 gene, encoding the g subunit, did not affect cell growth or glucose consumption, but biomass production was lower in the mutant strain (gΔ strain). Ultrastructure observations showed that mitochondrial size and cristae shape were similar in wild-type and gΔ strains. The mitochondrial membrane potential in both strains had a similar magnitude, but oxygen consumption was higher in the WT strain. ATP synthesis was 20 % lower in the gΔ strain. Additionally, the mutant strain expressed the alternative oxidase in the early stages of growth (exponential phase), probably as a response to ROS stress. Dimer from mutant strain was unstable to digitonin solubilization, avoiding its isolation and kinetic characterization. The isolated monomeric state activated by n-dodecyl-β-D-maltopyranoside showed similar kinetic constants to the monomer from the WT strain. A decrease in mitochondrial ATP synthesis and the presence of the AOX during the exponential growth phase suggests that deletion of the g gene induces ROS stress.

Application of Molecular Simulation Methods in Food Science: Status and Prospects

Molecular simulation methods, such as molecular docking, molecular dynamic (MD) simulation, and quantum chemical (QC) calculation, have become popular as characterization and/or virtual screening tools because they can visually display interaction details that in vitro experiments can not capture and quickly screen bioactive compounds from large databases with millions of molecules. Currently, interdisciplinary research has expanded molecular simulation technology from computer aided drug design (CADD) to food science. More food scientists are supporting their hypotheses/results with this technology. To understand better the use of molecular simulation methods, it is necessary to systematically summarize the latest applications and usage trends of molecular simulation methods in the research field of food science. However, this type of review article is rare. To bridge this gap, we have comprehensively summarized the principle, combination usage, and application of molecular simulation methods in food science. We also analyzed the limitations and future trends and offered valuable strategies with the latest technologies to help food scientists use molecular simulation methods.

Characterization of the enzymatic and multifunctional properties of Acinetobacter baumannii erythrose-4-phosphate dehydrogenase (E4PDH)

Infections due to Acinetobacter baumannii (A. baumannii) are rapidly increasing worldwide and consequently therapeutic options for treatment are limited. The emergence of multi drug resistant (MDR) strains has rendered available antibiotics ineffective, necessitating the urgent discovery of new drugs and drug targets. The vitamin B6 biosynthetic pathway has been considered as a potential antibacterial drug target but it is as yet uncharacterized for A. baumannii. In the current work, we have carried out in silico and biochemical characterization of Erythrose-4-phosphate dehydrogenase (E4PDH) (EC 1.2.1.72). This enzyme catalyzes the first step in the deoxyxylulose-5-phosphate (DXP) dependent Vitamin B6 biosynthetic pathway i.e. the conversion of d-erythrose-4-phosphate (E4P) to 4-Phosphoerythronate. E4PDH also possesses an additional activity whereby it can catalyze the conversion of Glyceraldehyde-3-phosphate (G3P) to 1,3 bisphosphoglycerate (1,3BPG). Our studies have revealed that this enzyme exhibits an alternate moonlighting function as a cell surface receptor for the human iron transport proteins transferrin (Tf) and lactoferrin (Lf). The present work reports the internalization of Tf and consequent iron acquisition as an alternate strategy for iron acquisition. Given its essential role in two crucial pathways i.e. metabolism and iron acquisition, A. baumannii E4PDH may play a vital role in bacterial pathogenesis.

Structural basis of constitutive c-Src kinase activity due to R175L and W118A mutations

Cellular Src (c-Src) belongs to a non-receptor membrane-associated tyrosine kinase family that plays essential roles in cellular processes. Growing evidence suggests that R175L and W118A mutations in SH2/SH3 domains of c-Src functionally inactivate these domains leading to constitutive activation of kinase domain (KD). Here we modeled c-Src^R175L, c-Src^W118A and c-Src^W118A+R175L structures by inducing phosphorylation at Y416 or Y527, respectively to characterize the comparative dynamics in the active versus inactive states through molecular dynamics simulation assay. We observed more conformational readjustments in c-Src^open than its close variants. In particular, C-terminal tail residues of c-Src^W118A-open and c-Src^{W118A+R175L-open} demonstrate significantly higher transitions. The cross-correlation analysis revealed an anticorrelation behavior in the motion of KD with respect to SH2, SH3 and the linker region of Src^{W118A+R175L-open}, while in c-Src^WT-open, SH2 and SH3 domains were anticorrelated, while KD and C-terminal tail motions were correlated. Due to these conformational differences, c-Src open forms exhibited lower interaction between pY527 and SH2 domain. Through detailed structural analysis, we observed a uniform myristate binding cavity in c-Src^WT-open, while the myristoyl pockets of mutant forms were deformed. We propose that constitutive activation of mutant Src forms may presumably be achieved by the prolonged membrane binding due to unusual conformations of C-terminal and myristoyl switch residues that may result in a higher dephosphorylation rate at pY527 in the myristoylated c-Src. Thus, our study establishes novel clues to decipher the constitutive activation status of c-Src in response to known mutations that may help in devising novel therapeutic strategies for cancer metastasis treatment.Communicated by Ramaswamy H. Sarma.

A systematic drug repurposing approach to identify promising inhibitors from FDA-approved drugs against Nsp4 protein of SARS-CoV-2

COVID-19 is caused by SARS-CoV-2 and responsible for the ongoing global pandemic in the world. After more than a year, we are still in lurch to combat and control the situation. Therefore, new therapeutic options to control the ongoing COVID-19 are urgently in need. In our study, we found that nonstructural protein 4 (Nsp4) of SARS-CoV-2 could be a potential target for drug repurposing. Due to availability of only the crystal structure of C-terminal domain of Nsp4 (Ct-Nsp4) and its crucial participation in viral RNA synthesis, we have chosen Ct-Nsp4 as a target for screening the 1600 FDA-approved drugs using molecular docking. Top 102 drugs were found to have the binding energy equal or less than -7.0 kcal/mol. Eribulin and Suvorexant were identified as the two most promising drug molecules based on the docking score. The dynamics of Ct-Nsp4-drug binding was monitored using 100 ns molecular dynamics simulations. From binding free energy calculation over the simulation, both the drugs were found to have considerable binding energy. The present study has identified Eribulin and Suvorexant as promising drug candidates. This finding will be helpful to accelerate the drug discovery process against COVID-19 disease.Communicated by Ramaswamy H. Sarma.

Computational investigation of potent inhibitors against YsxC: structure-based pharmacophore modeling, molecular docking, molecular dynamics, and binding free energy

In S. aureus, ribosome biogenesis GTP-binding (YsxC), a GTPase interacts with 50S subunit and 30S subunit of ribosome, and β' subunit of RNA polymerase and played an important role in protein synthesis. For the identification of potent lead molecules, we have conducted pharmacophore modeling by consideration of pharmacophore features of GTP among YsxC-GTP complex. Virtual screening and molecular docking results displayed that five pharmacokinetic and ADMET filtered molecules-ZINC000006424138, ZINC000095502032, ZINC000225415132, ZINC000095475800, and ZINC000012990761-had higher binding affinities than GTP with YsxC. All the identified molecules shared similar pharmacophore features of GTP and were stabilized via hydrogen bonds and hydrophobic interactions with YsxC. Molecular dynamics analysis revealed that YsxC-inhibitor(s) complexes were lesser dynamics and higher stable than YsxC-GTP complex. Molecular Mechanics/Poisson-Boltzmann Surface Area (MMPBSA) results confirmed that identified molecules bound at the active site (Arg33, Ser34, Asn35, Val36, Lys38, Ser39, Thr40, Thr54, Ser55, Pro58, Lys60, Thr61, Thr144, Lys145, Ser178, and Ile179) of YsxC and formed the lower energy (-190.32 ± 3.46 to -217.03 ± 2.55 kJ/mol) complexes than YsxC-GTP (-157.16 ± 2.89 kJ/mol) complex. The identified molecules in this study can be further tested and utilized to design novel antimicrobial agents for S. aureus.Communicated by Ramaswamy H. Sarma.

Virtual screening of gut microbiome bacteriocins as potential inhibitors of stearoyl-CoA desaturase 1 to regulate adipocyte differentiation and thermogenesis to combat obesity

The gut bacterial strains and their metabolites have been shown to play a significant role in obesity, but the molecular mechanisms underlying this association are largely unresolved. Obesity is a multifactorial problem and is controlled by various mechanisms and pathways to produce and store fat cells. Bacteriocins are secondary metabolites produced by gut bacteria to defend themselves against their competitors. Recently, they have gained great attention due to their role in metabolic disorders, including obesity. Stearoyl-CoA desaturase 1 (SCD1) is a key enzyme involved in the differentiation of adipocytes. The aim of this study is to show the regulation of SCD1 by bacteriocins and thus their importance in obesity control. We screened the human gut bacteriome for the presence of bacteriocins, predicted their structures, and showed their inhibitory role by molecular docking with SCD1. Further, to confirm the docking results, MDS of six top scoring SCD1-bacteriocin complexes were carried out for 100 ns. These six bacteriocins namely, Plantaricin S-beta, Carnolysin, Lactococcin B, Bacteriocin Iic, Plantaricin N, and Thermophilin A, with strong binding affinities, are primarily produced by bacterial strains from the Lactobacillaeacea family. These findings can be the basis of further experiments for enhanced understanding of the underlying mechanisms for obesity control, specifically bacteriocins driven regulation of the SCD1 enzyme. In addition, a consortium of bacterial strains producing these bacteriocins can be developed and used as probiotics for the amelioration of obesity and other metabolic complications.Communicated by Ramaswamy H. Sarma.

New simulation insights on the structural transition mechanism of bovine rhodopsin activation

Inactive rhodopsin can absorb photons, which induces different structural transitions that finally activate rhodopsin. We have examined the change in spatial configurations and physicochemical factors that result during the transition mechanism from the inactive to the active rhodopsin state via intermediates. During the activation process, many existing atomic contacts are disrupted, and new ones are formed. This is related to the movement of Helix 5, which tilts away from Helix 3 in the intermediate state in lumirhodopsin and moves closer to Helix 3 again in the active state. Similar patterns of changing atomic contacts are observed between Helices 3 and 5 of the adenosine and neurotensin receptors. In addition, residues 220-238 of rhodopsin, which are disordered in the inactive state, fold in the active state before binding to the Gα, where it catalyzes GDP/GTP exchange on the Gα subunit. Finally, molecular dynamics simulations in the membrane environment revealed that the arrestin binding region adopts a more flexible extended conformation upon phosphorylation, likely promoting arrestin binding and inactivation. In summary, our results provide additional structural understanding of specific rhodopsin activation which might be relevant to other Class A G protein-coupled receptor proteins.

Molecular dynamic simulation and functional analysis of pathogenic PTEN mutations in glioblastoma

PTEN, a dual-phosphatase and scaffold protein, is one of the most commonly mutated tumour suppressor gene across various cancer types in human. The aim of this study therefore was to investigate the stability, structural and functional effects, and pathogenicity of 12 missense PTEN mutations (R15S, E18G, G36R, N49I, Y68H, I101T, C105F, D109N, V133I, C136Y, R173C and N276S) found by next generation sequencing of the PTEN gene in tissue samples obtained from glioblastoma patients. Computational tools and molecular dynamic simulation programs were used to identify the deleterious effects of these mutations. Furthermore, PTEN mRNA and protein expression levels were evaluated by qRT-PCR, Western Blot, and immunohistochemistry staining methods. Various computational tools predicted strong deleterious effects for the G36R, C105F, C136Y and N276S mutations. Molecular dynamic simulation revealed a significant decrease in protein stability for the Y68H and N276S mutations when compared with the wild type protein; whereas, C105F, D109N, V133I and R173C showed partial stability reduction. Significant residual fluctuations were observed in the R15S, N49I and C136Y mutations and radius of gyration graphs revealed the most compact structure for D109N and least for C136Y. In summary, our study is the first one to show the presence of PTEN E18G, N49I, D109N and N276S mutations in glioblastoma patients; where, D109N is neutral and N276S is a damaging and disease-associated mutation.Communicated by Ramaswamy H. Sarma.

Molecular dynamics simulation study on the structures of fascin mutants

Fascin is a filamentous actin (F-actin) bundling protein, which cross-links F-actin into bundles and becomes an important component of filopodia on the cell surface. Fascin is overexpressed in many types of cancers. The mutation of fascin affects its ability to bind to F-actin and the progress of cancer. In this paper, we have studied the effects of residues of K22, K41, K43, K241, K358, K399, and K471 using molecular dynamics (MD) simulation. For the strong-effect residues, that is, K22, K41, K43, K358, and K471, our results show that the mutation of K to A leads to large values of root mean square fluctuation (RMSF) around the mutated residues, indicating those residues are important for the flexibility and thermal stability. On the other hand, based on residue cross-correlation analysis, alanine mutations of these residues reinforce the correlation between residues. Together with the RMSF data, the local flexibility is extended to the entire protein by the strong correlations to influence the dynamics and function of fascin. By contrast, for the mutants of K241A and K399A those do not affect the function of fascin, the RMSF data do not show significant differences compared with wild-type fascin. These findings are in a good agreement with experimental studies.

Quality Estimates for 3D Protein Models

Protein structure modeling is one of the most advanced and complex processes in computational biology. One of the major problems for the protein structure prediction field has been how to estimate the accuracy of the predicted 3D models, on both a local and global level, in the absence of known structures. We must be able to accurately measure the confidence that we have in the quality predicted 3D models of proteins for them to become widely adopted by the general bioscience community. To address this major issue, it was necessary to develop new model quality assessment (MQA) methods and integrate them into our pipelines for building 3D protein models. Our MQA method, called ModFOLD, has been ranked as one of the most accurate MQA tools in independent blind evaluations. This chapter discusses model quality assessment in the protein modeling field, demonstrating both its strengths and limitations. We also present some of the best methods according to independent benchmarking data, which has been gathered in recent years.

In silico analysis of peroxidase from Luffa acutangula

Peroxidases are oxidoreductase enzymes that widely gained attention as biocatalysts for their robust catalytic activity, specificity, and regioselective functionality for phenolic compounds. The study of molecular aspects of peroxidases is as crucial as that of the physicochemical aspects. A bioinformatics approach is utilized in this study to investigate the structural aspects and functions of luffa peroxidase (LPrx) from Luffa acutangula. The evolutionary relationship of LPrx with other class III peroxidases was studied by constructing a neighbour-joining phylogenetic tree. An analysis of the phylogenetic tree revealed that plant peroxidases share a common ancestor. The gene ontology term showed that LPrx had a molecular functionality of the oxidation-reduction process, heme binding and peroxidase-like activity, and the biological function of hydrogen peroxide scavenging activity. The enzyme-ligand interactions were studied from a catalytic point of view using the molecular docking technique. The molecular docking was carried out with LPrx as a receptor and guaiacol, m-cresol, p-cresol, catechol, quinol, pyrogallol, 2,4-dimethoxyphenol, gallic acid, aniline, and o-phenylenediamine as ligands. The results presented in the current communication will have a significant implication in proteomics, biochemistry, biotechnology, and the potential applications of peroxidases in the biotransformations of organic compounds.

Supplementary Information

The online version contains supplementary material available at 10.1007/s13205-022-03432-8.

Illuminating the "Twilight Zone": Advances in Difficult Protein Modeling

Homology modeling was long considered a method of choice in tertiary protein structure prediction. However, it used to provide models of acceptable quality only when templates with appreciable sequence identity with a target could be found. The threshold value was long assumed to be around 20-30%. Below this level, obtained sequence identity was getting dangerously close to values that can be obtained by chance, after aligning any random, unrelated sequences. In these cases, other approaches, including ab initio folding simulations or fragment assembly, were usually employed. The most recent editions of the CASP and CAMEO community-wide modeling methods assessment have brought some surprising outcomes, proving that much more clues can be inferred from protein sequence analyses than previously thought. In this chapter, we focus on recent advances in the field of difficult protein modeling, pushing the threshold deep into the "twilight zone", with particular attention devoted to improvements in applications of machine learning and model evaluation.

Molecular modeling and dynamics simulation of alcohol dehydrogenase enzyme from high efficacy cellulosic ethanol-producing yeast mutant strain Pichia kudriavzevii BGY1-γm

One of the major constraints limiting the use of abundantly available lignocellulosic biomass as potential feedstock for alcohol industry is the lack of C₆/C₅ co-sugar fermenting yeast. The present study explores a mutant yeast Pichia kudriavzevii BGY1-γm as a potential strain for bioconversion of glucose/xylose sugars of green biomass into ethanol under batch fermentation. The mutant strain having higher alcohol dehydrogenase activity (11.31%) showed significantly higher ethanol concentration during co-fermentation of glucose/xylose sugars (14.2%) as compared to the native strain. Based on 99% sequence similarity of ADH encoding gene from the mutant with the gene sequences from other yeast strains, the ADH enzyme was identified as ADH-1 type. The study reveals first three-dimensional model of ADH-1 utilizing glucose/xylose sugars from P. kudriavzevii BGY1-γm (PkADH mutant). The refined and validated model of PkADH mutant was used for molecular docking against the substrate (acetaldehyde) and product (ethanol). Molecular docking results showed that substrate and product exhibited a binding affinity of -4.55 and -4.5 kcal/mol with PkADH mutant. Acetaldehyde and ethanol interacted at the active site of PkADH mutant via hydrogen bonds (Ser42, His69 and Asp163) and hydrophobic interactions (Cys40, Ser42, His69, Cys95, Trp123 and Asp163) to form the stable protein-ligand complex. Molecular dynamics analysis revealed that PkADH-mutant acetaldehyde and PkADH-mutant ethanol complexes were more stable than PkADH mutant. MMPBSA binding energy confirmed that binding of substrate and product results in the formation of a lower energy stable protein-ligand complex.Communicated by Ramaswamy H. Sarma.

Gabapentin Disrupts Binding of Perlecan to the α2δ1 Voltage Sensitive Calcium Channel Subunit and Impairs Skeletal Mechanosensation

Our understanding of how osteocytes, the principal mechanosensors within bone, sense and perceive force remains unclear. Previous work identified "tethering elements" (TEs) spanning the pericellular space of osteocytes and transmitting mechanical information into biochemical signals. While we identified the heparan sulfate proteoglycan perlecan (PLN) as a component of these TEs, PLN must attach to the cell surface to induce biochemical responses. As voltage-sensitive calcium channels (VSCCs) are critical for bone mechanotransduction, we hypothesized that PLN binds the extracellular α₂δ₁ subunit of VSCCs to couple the bone matrix to the osteocyte membrane. Here, we showed co-localization of PLN and α₂δ₁ along osteocyte dendritic processes. Additionally, we quantified the molecular interactions between α₂δ₁ and PLN domains and demonstrated for the first time that α₂δ₁ strongly associates with PLN via its domain III. Furthermore, α₂δ₁ is the binding site for the commonly used pain drug, gabapentin (GBP), which is associated with adverse skeletal effects when used chronically. We found that GBP disrupts PLN::α₂δ₁ binding in vitro, and GBP treatment in vivo results in impaired bone mechanosensation. Our work identified a novel mechanosensory complex within osteocytes composed of PLN and α₂δ₁, necessary for bone force transmission and sensitive to the drug GBP.

The in silico and in vitro analysis of donepezil derivatives for Anopheles acetylcholinesterase inhibition

Current studies on Anopheles anticholinesterase insecticides are focusing on identifying agents with high selectivity towards Anopheles over mammalian targets. Acetylcholinesterase (AChE) from electric eel is often used as the bioequivalent enzyme to study ligands designed for activity and inhibition in human. In this study, previously identified derivatives of a potent AChE, donepezil, that have exhibited low activity on electric eel AChE were assessed for potential AChE-based larvicidal effects on four African malaria vectors; An. funestus, An. arabiensis, An. gambiae and An. coluzzii. This led to the identification of four larvicidal agents with a lead molecule, 1-benzyl-N-(thiazol-2-yl) piperidine-4-carboxamide 2 showing selectivity for An. arabiensis as a larvicidal AChE agent. Differential activities of this molecule on An. arabiensis and electric eel AChE targets were studied through molecular modelling. Homology modelling was used to generate a three-dimensional structure of the An. arabiensis AChE for this binding assay. The conformation of this molecule and corresponding interactions with the AChE catalytic site was markedly different between the two targets. Assessment of the differences between the AChE binding sites from electric eel, human and Anopheles revealed that the electric eel and human AChE proteins were very similar. In contrast, Anopheles AChE had a smaller cysteine residue in place of bulky phenylalanine group at the entrance to the catalytic site, and a smaller aspartic acid residue at the base of the active site gorge, in place of the bulky tyrosine residues. Results from this study suggest that this difference affects the ligand orientation and corresponding interactions at the catalytic site. The lead molecule 2 also formed more favourable interactions with An. arabiensis AChE model than other Anopheles AChE targets, possibly explaining the observed selectivity among other assessed Anopheles species. This study suggests that 1-benzyl-N-(thiazol-2-yl) piperidine-4-carboxamide 2 may be a lead compound for designing novel insecticides against Anopheles vectors with reduced toxic potential on humans.

Mycobacterium tuberculosis dormancy regulon proteins Rv2627c and Rv2628 as Toll like receptor agonist and as potential adjuvant

During latency, DosR proteins of Mycobacterium tuberculosis (M.tb) get activated and help the bacterium to remain dormant. We have shown earlier that 2 such proteins Rv2627c and Rv2628 are immunogenic and induce a TH1 kind of immune response. In this study, through in-vitro experiments we have confirmed that Rv2627c and Rv2628 proteins act as protein Toll-Like Receptor (TLR) agonist-adjuvant. Rv2627c and Rv2628 stimulated THP-1 macrophages showed an increased expression of TLR2, TLR4 and co-stimulatory molecules CD40, CD80, CD86 and antigen presenting molecule HLA-DR. Further studies also found enhanced expression of downstream signaling molecules of TLR activation like MyD88, NF-κB-p65 and pro-inflammatory cytokines. Inhibition studies using TLR blocking antibodies decreased the expression of co-stimulatory molecules, MyD88, NF-κB-p65, and pro-inflammatory cytokines. Rv2627c and Rv2628 stimulation of HEK-TLR2 reporter cell line confirmed the interaction of these proteins with TLR2. Moreover, molecular docking and simulations of Rv2627c and Rv2628 proteins with TLR2 and TLR4 showed stable interactions. The adjuvant activity of Rv2628 was further validated by a protein adjuvanted with pre-clinically validated peptides as multi-epitope vaccine construct which showed good binding with TLR2 and TLR4 and activate dendritic cells and induce sustained pro-inflammatory cytokine response by C-ImmSim analysis. We propose that our vaccine construct will produce a better immune response than BCG and can be taken up as a post-exposure therapeutic subunit vaccine along with standard TB therapy. We also anticipate that our construct can be taken up as a protein adjuvant with other vaccine candidates as these can activate macrophages through TLR signaling.

Novel Insights into Understanding the Molecular Dialogues between Bipolaroxin and the Gα and Gβ Subunits of the Wheat Heterotrimeric G-Protein during Host–Pathogen Interaction

Spot blotch disease of wheat, caused by the fungus Bipolaris sorokiniana (Sacc.) Shoem., produces several toxins which interact with the plants and thereby increase the blightening of the wheat leaves, and Bipolaroxin is one of them. There is an urgent need to decipher the molecular interaction between wheat and the toxin Bipolaroxin for in-depth understanding of host–pathogen interactions. In the present study, we have developed the three-dimensional structure of G-protein alpha subunit from Triticum aestivum. Molecular docking studies were performed using the active site of the modeled G-protein alpha and cryo-EM structure of beta subunit from T. aestivum and ‘Bipolaroxin’. The study of protein–ligand interactions revealed that six H-bonds are mainly formed by Glu29, Ser30, Lys32, and Ala177 of G-alpha with Bipolaroxin. In the beta subunit, the residues of the core beta strand domain participate in the ligand interaction where Lys256, Phe306, and Leu352 formed seven H-bonds with the ligand Bipolaroxin. All-atoms molecular dynamics (MD) simulation studies were conducted for G-alpha and -beta subunit and Bipolaroxin complexes to explore the stability, conformational flexibility, and dynamic behavior of the complex system. In planta studies clearly indicated that application of Bipolaroxin significantly impacted the physio-biochemical pathways in wheat and led to the blightening of leaves in susceptible cultivars as compared to resistant ones. Further, it interacted with the Gα and Gβ subunits of G-protein, phenylpropanoid, and MAPK pathways, which is clearly supported by the qPCR results. This study gives deeper insights into understanding the molecular dialogues between Bipolaroxin and the Gα and Gβ subunits of the wheat heterotrimeric G-protein during host–pathogen interaction.

BESFA: bioinformatics based evolutionary, structural & functional analysis of prostrate, Placenta, Ovary, Testis, and Embryo (POTE) paralogs

The POTE family comprises 14 paralogues and is primarily expressed in Prostrate, Placenta, Ovary, Testis, Embryo (POTE), and cancerous cells. The prospective function of the POTE protein family under physiological conditions is less understood. We systematically analyzed their cellular localization and molecular docking analysis to elucidate POTE proteins' structure, function, and Adaptive Divergence. Our results suggest that group three POTE paralogs (POTEE, POTEF, POTEI, POTEJ, and POTEKP (a pseudogene)) exhibits significant variation among other members could be because of their Adaptive Divergence. Furthermore, our molecular docking studies on POTE protein revealed the highest binding affinity with NCI-approved anticancer compounds. Additionally, POTEE, POTEF, POTEI, and POTEJ were subject to an explicit molecular dynamic simulation for 50ns. MM-GBSA and other essential electrostatics were calculated that showcased that only POTEE and POTEF have absolute binding affinities with minimum energy exploitation. Thus, this study’s outcomes are expected to drive cancer research to successful utilization of POTE genes family as a new biomarker, which could pave the way for the discovery of new therapies.

Estimation of model accuracy by a unique set of features and tree-based regressor

Computationally generated models of protein structures bridge the gap between the practically negligible price tag of sequencing and the high cost of experimental structure determination. By providing a low-cost (and often free) partial alternative to experimentally determined structures, these models help biologists design and interpret their experiments. Obviously, the more accurate the models the more useful they are. However, methods for protein structure prediction generate many structural models of various qualities, necessitating means for the estimation of their accuracy. In this work we present MESHI_consensus, a new method for the estimation of model accuracy. The method uses a tree-based regressor and a set of structural, target-based, and consensus-based features. The new method achieved high performance in the EMA (Estimation of Model Accuracy) track of the recent CASP14 community-wide experiment (https://predictioncenter.org/casp14/index.cgi). The tertiary structure prediction track of that experiment revealed an unprecedented leap in prediction performance by a single prediction group/method, namely AlphaFold2. This achievement would inevitably have a profound impact on the field of protein structure prediction, including the accuracy estimation sub-task. We conclude this manuscript with some speculations regarding the future role of accuracy estimation in a new era of accurate protein structure prediction.