Consistent View of Protein Fluctuations from All-Atom Molecular Dynamics and Coarse-Grained Dynamics with Knowledge-Based Force-Field

Enhanced thermal stability enables human mismatch-specific thymine-DNA glycosylase to catalyse futile DNA repair

Human thymine-DNA glycosylase (TDG) excises T mispaired with G in a CpG context to initiate the base excision repair (BER) pathway. TDG is also involved in epigenetic regulation of gene expression by participating in active DNA demethylation. Here we demonstrate that under extended incubation time the full-length TDG (TDGFL), but neither its isolated catalytic domain (TDGcat) nor methyl-CpG binding domain-containing protein 4 (MBD4) DNA glycosylase, exhibits significant excision activity towards T and C in regular non-damaged DNA duplex in TpG/CpA and CpG/CpG contexts. Time course of the cleavage product accumulation under single-turnover conditions shows that the apparent rate constant for TDGFL-catalysed excision of T from T•A base pairs (0.0014-0.0069 min-1) is 85-330-fold lower than for the excision of T from T•G mispairs (0.47-0.61 min-1). Unexpectedly, TDGFL, but not TDGcat, exhibits prolonged enzyme survival at 37°C when incubated in the presence of equimolar concentrations of a non-specific DNA duplex, suggesting that the disordered N- and C-terminal domains of TDG can interact with DNA and stabilize the overall conformation of the protein. Notably, TDGFL was able to excise 5-hydroxymethylcytosine (5hmC), but not 5-methylcytosine residues from duplex DNA with the efficiency that could be physiologically relevant in post-mitotic cells. Our findings demonstrate that, under the experimental conditions used, TDG catalyses sequence context-dependent removal of T, C and 5hmC residues from regular DNA duplexes. We propose that in vivo the TDG-initiated futile DNA BER may lead to formation of persistent single-strand breaks in non-methylated or hydroxymethylated chromatin regions.

Exploring protein functions from structural flexibility using CABS-flex modeling

Understanding protein function often necessitates characterizing the flexibility of protein structures. However, simulating protein flexibility poses significant challenges due to the complex dynamics of protein systems, requiring extensive computational resources and accurate modeling techniques. In response to these challenges, the CABS-flex method has been developed as an efficient modeling tool that combines coarse-grained simulations with all-atom detail. Available both as a web server and a standalone package, CABS-flex is dedicated to a wide range of users. The web server version offers an accessible interface for straightforward tasks, while the standalone command-line program is designed for advanced users, providing additional features, analytical tools, and support for handling large systems. This paper examines the application of CABS-flex across various structure-function studies, facilitating investigations into the interplay among protein structure, dynamics, and function in diverse research fields. We present an overview of the current status of the CABS-flex methodology, highlighting its recent advancements, practical applications, and forthcoming challenges.

Aggrescan4D: structure-informed analysis of pH-dependent protein aggregation

Protein aggregation is behind the genesis of incurable diseases and imposes constraints on drug discovery and the industrial production and formulation of proteins. Over the years, we have been advancing the Aggresscan3D (A3D) method, aiming to deepen our comprehension of protein aggregation and assist the engineering of protein solubility. Since its inception, A3D has become one of the most popular structure-based aggregation predictors because of its performance, modular functionalities, RESTful service for extensive screenings, and intuitive user interface. Building on this foundation, we introduce Aggrescan4D (A4D), significantly extending A3D's functionality. A4D is aimed at predicting the pH-dependent aggregation of protein structures, and features an evolutionary-informed automatic mutation protocol to engineer protein solubility without compromising structure and stability. It also integrates precalculated results for the nearly 500,000 jobs in the A3D Model Organisms Database and structure retrieval from the AlphaFold database. Globally, A4D constitutes a comprehensive tool for understanding, predicting, and designing solutions for specific protein aggregation challenges. The A4D web server and extensive documentation are available at https://biocomp.chem.uw.edu.pl/a4d/. This website is free and open to all users without a login requirement.

Hotspot Wizard-informed engineering of a hyperthermophilic β-glucosidase for enhanced enzyme activity at low temperatures

Hyperthermophilic enzymes serve as an important source of industrial enzymes due to their high thermostability. Unfortunately, most hyperthermophilic enzymes suffer from reduced activity at low temperatures (e.g., ambient temperature), limiting their applicability. In addition, evolving hyperthermophilic enzymes to increase low temperature activity without compromising other desired properties is generally difficult. In the current study, a variant of β-glucosidase from Pyrococcus furiosus (PfBGL) was engineered to enhance enzyme activity at low temperatures through the construction of a saturation mutagenesis library guided by the HotSpot Wizard analysis, followed by its screening for activity and thermostability. From this library construction and screening, one PfBGL mutant, PfBGL-A4 containing Q214S/A264S/F344I mutations, showed an over twofold increase in β-glucosidase activity at 25 and 50°C compared to the wild type, without compromising high-temperature activity, thermostability and substrate specificity. Our experimental and computational characterizations suggest that the findings with PfBGL-A4 may be due to the elevation of local conformational flexibility around the active site, while slightly compacting the global protein structure. This study showcases the potential of HotSpot Wizard-informed engineering of hyperthermophilic enzymes and underscores the interplays among temperature, enzyme activity, and conformational flexibility in these enzymes.

New oxomethacrylate and acetamide: synthesis, characterization, and their computational approaches: molecular docking, molecular dynamics, and ADME analyses

The compounds 2-chloro-N-(3-methoxyphenyl)acetamide (m-acetamide) and 2-(3-methoxyphenylamino)-2-oxoethyl methacrylate (3MPAEMA) were synthesized in this study for the first time in the literature. FTIR, 1H, and 13C NMR spectroscopic techniques were used to characterize it. Subsequently, computational techniques were used to assess various ADME factors, such as drug-likeness properties, bioavailability score, and adherence to Lipinski's rule. Finally, molecular docking experiments were conducted with the human topoisomerase α2 (TOP2A) protein to verify and validate the reliability and stability of the docking procedure. The results of the docking scores, which quantify binding affinity, indicated that these derivatives exhibited a stronger affinity for TOP2A.

Structure prediction of linear and cyclic peptides using CABS-flex

The structural modeling of peptides can be a useful aid in the discovery of new drugs and a deeper understanding of the molecular mechanisms of life. Here we present a novel multiscale protocol for the structure prediction of linear and cyclic peptides. The protocol combines two main stages: coarse-grained simulations using the CABS-flex standalone package and an all-atom reconstruction-optimization process using the Modeller program. We evaluated the protocol on a set of linear peptides and two sets of cyclic peptides, with cyclization through the backbone and disulfide bonds. A comparison with other state-of-the-art tools (APPTEST, PEP-FOLD, ESMFold and AlphaFold implementation in ColabFold) shows that for most cases, AlphaFold offers the highest resolution. However, CABS-flex is competitive, particularly when it comes to short linear peptides. As demonstrated, the protocol performance can be further improved by combination with the residue-residue contact prediction method or more efficient scoring. The protocol is included in the CABS-flex standalone package along with online documentation to aid users in predicting the structure of peptides and mini-proteins.

Molecular docking-based virtual screening, drug-likeness, and pharmacokinetic profiling of some anti-Salmonella typhimurium cephalosporin derivatives

Objective

The rising cases of resistance to existing antibiotic therapies in Salmonella typhimurium has made it necessary to search for novel drug candidates. The present study employed the molecular docking technique to screen a set of antibacterial cephalosporin analogues against penicillin-binding protein 1a (PBP1a) of the bacterium. This is the first study to screen cephalosporin analogues against PBP1a, a protein central to peptidoglycan synthesis in S. typhimurium.

Methods

Some cephalosporin analogues were retrieved from a drug repository. The structures of the molecules were optimized using the semi-empirical method of Spartan 14 software and were subsequently docked against the active sites of PBP1a using AutoDock vina software. The most potent ligands were chosen as the most promising leads and subsequently subjected to absorption, distribution, metabolism, excretion, and toxicity (ADMET) profiling using the SwissADME online server and DataWarrior chemoinformatics program. The CABSflex 2.0 server was used to carry out molecular dynamics (MD) simulation on the most stable ligand-protein complex.

Results

Compounds 3, 23, and 28 with binding affinity (ΔG) values of -9.2, -8.7, and -8.9 kcal/mol, respectively, were selected as the most promising leads. The ligands bound to the active sites of PBP1a via hydrophobic bonds, hydrogen bonds, and electrostatic interactions. Furthermore, ADMET analyses of the ligands revealed that they exhibited sound pharmacokinetic and toxicity profiles. In addition, an MD study revealed that the most active ligand bound favorably and dynamically to the target protein.

Conclusion

The findings of this research could provide an excellent platform for the discovery and rational design of novel antibiotics against S. typhimurium. Additional in vitro and in vivo studies should be carried out on the drug candidates to validate the findings of this study.

Investigation of the impact of nonsynonymous mutations on thyroid peroxidase dimer

Congenital hypothyroidism is one of the most common preventable endocrine disorders associated with thyroid dysgenesis or dyshormonogenesis. Thyroid peroxidase (TPO) gene defect is mainly responsible for dyshormonogenesis; a defect in the thyroid hormone biosynthesis pathway. In Bangladesh, there is limited data regarding the genetic etiology of Congenital Hypothyroidism (CH). The present study investigates the impact of the detected mutations (p.Ala373Ser, and p.Thr725Pro) on the TPO dimer protein. We have performed sequential molecular docking of H2O2 and I- ligands with both monomers of TPO dimer to understand the iodination process in thyroid hormone biosynthesis. Understanding homodimer interactions at the atomic level is a critical challenge to elucidate their biological mechanisms of action. The docking results reveal that mutations in the dimer severely disrupt its catalytic interaction with essential ligands. Molecular dynamics simulation has been performed to validate the docking results, thus realizing the consequence of the mutation in the biological system's mimic. The dynamics results expose that mutations destabilize the TPO dimer protein. Finally, principal component analysis exhibits structural and energy profile discrepancies in wild-type and mutant dimers. The findings of this study highlight that the mutations in TPO protein can critically affect the dimer structure and loss of enzymatic activity is persistent. Other factors also might influence the hormone synthesis pathway, which is under investigation.

Integrative modeling of diverse protein-peptide systems using CABS-dock

The CABS model can be applied to a wide range of protein-protein and protein-peptide molecular modeling tasks, such as simulating folding pathways, predicting structures, docking, and analyzing the structural dynamics of molecular complexes. In this work, we use the CABS-dock tool in two diverse modeling tasks: 1) predicting the structures of amyloid protofilaments and 2) identifying cleavage sites in the peptide substrates of proteolytic enzymes. In the first case, simulations of the simultaneous docking of amyloidogenic peptides indicated that the CABS model can accurately predict the structures of amyloid protofilaments which have an in-register parallel architecture. Scoring based on a combination of symmetry criteria and estimated interaction energy values for bound monomers enables the identification of protofilament models that closely match their experimental structures for 5 out of 6 analyzed systems. For the second task, it has been shown that CABS-dock coarse-grained docking simulations can be used to identify the positions of cleavage sites in the peptide substrates of proteolytic enzymes. The cleavage site position was correctly identified for 12 out of 15 analyzed peptides. When combined with sequence-based methods, these docking simulations may lead to an efficient way of predicting cleavage sites in degraded proteins. The method also provides the atomic structures of enzyme-substrate complexes, which can give insights into enzyme-substrate interactions that are crucial for the design of new potent inhibitors.

Molecular docking-based interaction studies on imidazo[1,2-a] pyridine ethers and squaramides as anti-tubercular agents

Development of new anti-tubercular agents is required in the wake of resistance to the existing and newly approved drugs through novel-validated targets like ATP synthase, etc. The major limitation of poor correlation between docking scores and biological activity by SBDD was overcome by a novel approach of quantitatively correlating the interactions of different amino acid residues present in the target protein structure with the activity. This approach well predicted the ATP synthase inhibitory activity of imidazo[1,2-a] pyridine ethers and squaramides (r = 0.84) in terms of Glu65b interactions. Hence, the models were developed on combined (r = 0.78), and training (r = 0.82) sets of 52, and 27 molecules, respectively. The training set model well predicted the diverse dataset (r = 0.84), test set (r = 0.755), and, external dataset (r_ext = 0.76). This model predicted three compounds from a focused library generated by incorporating the essential features of the ATP synthase inhibition with the pIC₅₀ values in the range of 0.0508-0.1494 µM. Molecular dynamics simulation studies ascertain the stability of the protein structure and the docked poses of the ligands. The developed model(s) may be useful in the identification and optimization of novel compounds against TB.

Membrane Cholesterol Inhibits Progesterone-Mediated Sperm Function through the Possible Involvement of ABHD2

Abhydrolase domain containing 2-acylglycerol lipase (ABHD2) was recently claimed as the membrane receptor of progesterone (P4) in sperm cells, mediating cell processes such as sperm chemotaxis and acrosome reaction. Here, we investigated the role of membrane cholesterol (Chol) on ABHD2-mediated human sperm chemotaxis. Human sperm cells were obtained from twelve normozoospemic healthy donors. ABHD2-Chol interaction was modelled by computational molecular-modelling (MM). Sperm membrane Chol content was depleted by incubating cells with cyclodextrin (CD) or augmented by the incubation with the complex between CD and Chol (CD:Chol). Cell Chol levels were quantified by liquid chromatography-mass spectrometry. Sperm migration upon P4 gradient was evaluated through the accumulation assay in a specific migration device. Motility parameters were evaluated by sperm class analyzer, whilst intracellular calcium concentration, acrosome reaction and mitochondrial membrane potential were evaluated with calcium orange, FITC-conjugated anti-CD46 antibody and JC-1 fluorescent probes, respectively. MM analysis showed the possible stable binding Chol to ABHD2, resulting in to major impact on the protein backbone flexibility. The treatment with CD was associated with a dose-dependent increase in sperm migration in a 160 nM P4 gradient, together with increase in sperm motility parameters and levels of acrosome reaction. The treatment with CD:Chol was associated with essentially opposite effects. Chol was, thus, suggested to inhibit P4-mediated sperm function through the possible inhibition of ABHD2.

Exploring the pharmacological aspects of natural phytochemicals against SARS-CoV-2 Nsp14 through an in silico approach

The severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2), possesses an important bifunctional nonstructural protein (nsp14) with a C-terminal N7-methyltransferase (N7-MTase) domain and an N-terminal domain with exoribonuclease (ExoN) activity that is required for maintaining high-fidelity viral replication. Viruses use the error-prone replication mechanism, which results in high mutation rates, to adapt quickly to stressful situations. The efficiency with which nsp14 removes mismatched nucleotides due to the presence of ExoN activity protects viruses from mutagenesis. We investigated the pharmacological role of the phytochemicals (Baicalein, Bavachinin, Emodin, Kazinol F, Lycorine, Sinigrin, Procyanidin A2, Tanshinone IIA, Tanshinone IIB, Tomentin A, and Tomentin E) against the highly conserved nsp14 protein using docking-based computational analyses in search of new potential natural drug targets. The selected eleven phytochemicals failed to bind the active site of N7-Mtase in the global docking study, while the local docking study identified the top five phytochemicals with high binding energy scores ranging from - 9.0 to - 6.4 kcal/mol. Procyanidin A2 and Tomentin A showed the highest docking score of - 9.0 and - 8.1 kcal/mol, respectively. Local docking of isoform variants was also conducted, yielding the top five phytochemicals, with Procyanidin A1 having the highest binding energy value of - 9.1 kcal/mol. The phytochemicals were later tested for pharmacokinetics and pharmacodynamics analysis for Absorption, Distribution, Metabolism, Excretion, and Toxicity (ADMET) which resulted in choosing Tomentin A as a potential candidate. The molecular dynamics simulations studies of nsp14 revealed significant conformational changes upon complex formation with the identified compound, implying that these phytochemicals could be used as safe nutraceuticals which will impart long-term immunological competence in the human population against CoVs.

Graphical Abstract

Supplementary Information

The online version contains supplementary material available at 10.1007/s40203-023-00143-7.

Molecular modelling and structure-activity relationship of a natural derivative of o-hydroxybenzoate as a potent inhibitor of dual NSP3 and NSP12 of SARS-CoV-2: in silico study

The nsp3 macrodomain and nsp12 (RdRp) enzymes are strongly implicated in the virulent regulation of the host immune response and viral replication of SARS-CoV-2, making them plausible therapeutic targets for mitigating infectivity. Remdesivir remains the only FDA-approved small-molecule inhibitor of the nsp12 in clinical conditions while none has been approved yet for the nsp3 macrodomain. In this study, 69,067 natural compounds from the IBScreen database were screened for efficacious potentials with mechanistic multitarget-directed inhibitory pharmacology against the dual targets using in silico approaches. Standard and extra precision (SP and XP) Maestro glide docking analyses were employed to evaluate their inhibitory interactions against the enzymes. Four compounds, STOCK1N-45901, 03804, 83408, 08377 consistently showed high XP scores against the respective targets and interacted strongly with pharmacologically essential amino acid and RNA residues, in better terms than the standard, co-crystallized inhibitors, GS-441524 and remdesivir. Further assessments through the predictions of ADMET and mutagenicity distinguished STOCK1N-45901, a natural derivative of o-hydroxybenzoate as the most promising candidate. The ligand maintained a good conformational and thermodynamic stability in complex with the enzymes throughout the trajectories of 100 ns molecular dynamics, indicated by RMSD, RMSF and radius of gyration plots. Its binding free energy, MM-GBSA was recorded as -54.24 and -31.77 kcal/mol against the respective enzyme, while its structure-activity relationships confer high probabilities as active antiviral, anti-inflammatory, antiinfection, antitussive and peroxidase inhibitor. The IBScreen database natural product, STOCK1N-45901 (2,3,4,5,6-pentahydroxyhexyl o-hydroxybenzoate) is thus recommended as a potent inhibitor of dual nsp3 and nsp12 of SARS-CoV-2 for further study. Communicated by Ramaswamy H. Sarma.

Beyond sequence: Structure-based machine learning

Recent breakthroughs in protein structure prediction demarcate the start of a new era in structural bioinformatics. Combined with various advances in experimental structure determination and the uninterrupted pace at which new structures are published, this promises an age in which protein structure information is as prevalent and ubiquitous as sequence. Machine learning in protein bioinformatics has been dominated by sequence-based methods, but this is now changing to make use of the deluge of rich structural information as input. Machine learning methods making use of structures are scattered across literature and cover a number of different applications and scopes; while some try to address questions and tasks within a single protein family, others aim to capture characteristics across all available proteins. In this review, we look at the variety of structure-based machine learning approaches, how structures can be used as input, and typical applications of these approaches in protein biology. We also discuss current challenges and opportunities in this all-important and increasingly popular field.

Molecular insights into MYO3A kinase domain variants explain variability in both severity and progression of DFNB30 hearing impairment

Hereditary hearing impairment (HI) is a common disease with the highest incidence among sensory defects. Several genes have been identified to affect stereocilia structure causing HI, including the unconventional myosin3A. Interestingly, we noticed that variants in MYO3A gene have been previously found to cause variable HI onset and severity. Using clinical exome sequencing, we identified a novel pathogenic variant p.(Lys50Arg) in the MYO3A kinase domain (MYO3A-KD). Previous in vitro studies supported its damaging effect as a 'kinase-dead' mutant. We further analyzed this variation through molecular dynamics which predicts that changes in flexibility of MYO3A structure would influence the protein-ATP binding properties. This Lys50Arg mutation segregated with congenital profound non-syndromic HI. To better investigate this variability, we collected previously identified MYO3A-KDs variants, p.(Tyr129Cys), p.(His142Gln) and p.(Pro189Thr), and built both wild type and mutant 3 D MYO3A-KD models to assess their impact on the protein structure and function. Our results suggest that KD mutations could either cause a congenital profound form of HI, when particularly affecting the kinase activity and preventing the auto-phosphorylation of the motor, or a late onset and progressive form, when partially or completely inactivating the MYO3A protein. In conclusion, we report a novel pathogenic variant affecting the ATP-binding site within the MYO3A-KD causing congenital profound HI. Through computational approaches we provide a deeper understanding on the correlation between the effects of MYO3A-KD mutations and the variable hearing phenotypes. To the best of our knowledge this is the first study to correlate mutations' genotypes with the variable phenotypes of DFNB30.Communicated by Ramaswamy H. Sarma.

Computational analysis of protein stability and allosteric interaction networks in distinct conformational forms of the SARS-CoV-2 spike D614G mutant: reconciling functional mechanisms through allosteric model of spike regulation

In this study, we used an integrative computational approach to examine molecular mechanisms underlying functional effects of the D614G mutation by exploring atomistic modeling of the SARS-CoV-2 spike proteins as allosteric regulatory machines. We combined coarse-grained simulations, protein stability and dynamic fluctuation communication analysis with network-based community analysis to examine structures of the native and mutant SARS-CoV-2 spike proteins in different functional states. Through distance fluctuations communication analysis, we probed stability and allosteric communication propensities of protein residues in the native and mutant SARS-CoV-2 spike proteins, providing evidence that the D614G mutation can enhance long-range signaling of the allosteric spike engine. By combining functional dynamics analysis and ensemble-based alanine scanning of the SARS-CoV-2 spike proteins we found that the D614G mutation can improve stability of the spike protein in both closed and open forms, but shifting thermodynamic preferences towards the open mutant form. Our results revealed that the D614G mutation can promote the increased number of stable communities and allosteric hub centers in the open form by reorganizing and enhancing the stability of the S1-S2 inter-domain interactions and restricting mobility of the S1 regions. This study provides atomistic-based view of allosteric communications in the SARS-CoV-2 spike proteins, suggesting that the D614G mutation can exert its primary effect through allosterically induced changes on stability and communications in the residue interaction networks.Communicated by Ramaswamy H. Sarma.

Predicted Structure and Functions of the Prototypic Alphaherpesvirus Herpes Simplex Virus Type-1 UL37 Tegument Protein

The alphaherpesvirus UL37 tegument protein is a highly conserved, multi-functional protein. Mutagenesis analysis delineated the UL37 domains necessary for retrograde transport and viral replication. Specifically, the amino-terminal 480 amino acids are dispensable for virus replication in epithelial cell culture, but it is unknown whether this amino-terminal deletion affects UL37 structure and intracellular transport in epithelial cells and neurons. To investigate the structure and function of UL37, we utilized multiple computational approaches to predict and characterize the secondary and tertiary structure and other functional features. The structure of HSV-1 UL37 and Δ481N were deduced using publicly available predictive algorithms. The predicted model of HSV-1 UL37 is a stable, multi-functional, globular monomer, rich in alpha helices, with unfolded regions within the linker and the C-tail domains. The highly flexible C-tail contains predicted binding sites to the dynein intermediate chain, as well as DNA and RNA. Predicted interactions with the cytoplasmic surface of the lipid membrane suggest UL37 is a peripheral membrane protein. The Δ481N truncation did not alter the predicted structure of the UL37 C-terminus protein and its predicted interaction with dynein. We validated these models by examining the replication kinetics and transport of the Δ481N virus toward the nuclei of infected epithelial and neuronal cells. The Δ481N virus had substantial defects in virus spread; however, it exhibited no apparent defects in virus entry and intracellular transport. Using computational analyses, we identified several key features of UL37, particularly the flexible unstructured tail; we then demonstrated that the UL37 C-terminus alone is sufficient to effectively transport the virus towards the nucleus of infected epithelial and neuronal cells.

A comprehensive in silico exploration of the impacts of missense variants on two different conformations of human pirin protein

BACKGROUND

Pirin, a member of the cupin superfamily, is an iron-binding non-heme protein. It acts as a coregulator of several transcription factors, especially the members of NFκB transcription factor family. Based on the redox state of its iron cofactor, it can assume two different conformations and thereby act as a redox sensor inside the nucleus. Previous studies suggested that pirin may be associated with cancer, inflammatory diseases as well as COVID-19 severities. Hence, it is important to explore the pathogenicity of its missense variants. In this study, we used a number of in silico tools to investigate the effects of missense variants of pirin on its structure, stability, metal cofactor binding affinity and interactions with partner proteins. In addition, we used protein dynamics simulation to elucidate the effects of selected variants on its dynamics. Furthermore, we calculated the frequencies of haplotypes containing pirin missense variants across five major super-populations (African, Admixed American, East Asian, European and South Asian).

RESULTS

Among a total of 153 missense variants of pirin, 45 were uniformly predicted to be pathogenic. Of these, seven variants can be considered for further experimental studies. Variants R59P and L116P were predicted to significantly destabilize and damage pirin structure, substantially reduce its affinity to its binding partners and alter pirin residue fluctuation profile via changing the flexibility of several key residues. Additionally, variants R59Q, F78V, G98D, V151D and L220P were found to impact pirin structure and function in multiple ways. As no haplotype was identified to be harboring more than one missense variant, further interrogation of the individual effects of these seven missense variants is highly recommended.

CONCLUSIONS

Pirin is involved in the transcriptional regulation of several genes and can play an important role in inflammatory responses. The variants predicted to be pathogenic in this study may thus contribute to a better understanding of the underlying molecular mechanisms of various inflammatory diseases. Future studies should be focused on clarifying if any of these variants can be used as disease biomarkers.

SUPPLEMENTARY INFORMATION

The online version contains supplementary material available at 10.1186/s42269-022-00917-7.

Conformational Dynamics and Mechanisms of Client Protein Integration into the Hsp90 Chaperone Controlled by Allosteric Interactions of Regulatory Switches: Perturbation-Based Network Approach for Mutational Profiling of the Hsp90 Binding and Allostery

Understanding the allosteric mechanisms of the Hsp90 chaperone interactions with cochaperones and client protein clientele is fundamental to dissect activation and regulation of many proteins. In this work, atomistic simulations are combined with perturbation-based approaches and dynamic network modeling for a comparative mutational profiling of the Hsp90 binding and allosteric interaction networks in the three Hsp90 maturation complexes with FKBP51 and P23 cochaperones and the glucocorticoid receptor (GR) client. The conformational dynamics signatures of the Hsp90 complexes and dynamics fluctuation analysis revealed how the intrinsic plasticity of the Hsp90 dimer can be modulated by cochaperones and client proteins to stabilize the closed dimer state required at the maturation stage of the ATPase cycle. In silico deep mutational scanning of the protein residues characterized the hot spots of protein stability and binding affinity in the Hsp90 complexes, showing that binding hot spots may often coincide with the regulatory centers that modulate dynamic allostery in the Hsp90 dimer. We introduce a perturbation-based network approach for mutational scanning of allosteric residue potentials and characterize allosteric switch clusters that control mechanism of cochaperone-dependent client recognition and remodeling by the Hsp90 chaperone. The results revealed a conserved network of allosteric switches in the Hsp90 complexes that allow cochaperones and GR protein to become integrated into the Hsp90 system by anchoring to the conformational switch points in the functional Hsp90 regions. This study suggests that the Hsp90 binding and allostery may operate under a regulatory mechanism in which activation or repression of the Hsp90 activity can be pre-encoded in the allosterically regulated Hsp90 dimer motions. By binding directly to the conformational switch centers on the Hsp90, cochaperones and interacting proteins can efficiently modulate the allosteric interactions and long-range communications required for client remodeling and activation.

Landscape-Based Protein Stability Analysis and Network Modeling of Multiple Conformational States of the SARS-CoV-2 Spike D614G Mutant: Conformational Plasticity and Frustration-Induced Allostery as Energetic Drivers of Highly Transmissible Spike Variants

The structural and functional studies of the SARS-CoV-2 spike protein variants revealed an important role of the D614G mutation that is shared across many variants of concern (VOCs), suggesting the effect of this mutation on the enhanced virus infectivity and transmissibility. The recent structural and biophysical studies provided important evidence about multiple conformational substates of the D614G spike protein. The development of a plausible mechanistic model that can explain the experimental observations from a more unified thermodynamic perspective is an important objective of the current work. In this study, we employed efficient and accurate coarse-grained simulations of multiple structural substates of the D614G spike trimers together with the ensemble-based mutational frustration analysis to characterize the dynamics signatures of the conformational landscapes. By combining the local frustration profiling of the conformational states with residue-based mutational scanning of protein stability and network analysis of allosteric interactions and communications, we determine the patterns of mutational sensitivity in the functional regions and sites of variants. We found that the D614G mutation may induce a considerable conformational adaptability of the open states in the SARS-CoV-2 spike protein without compromising the folding stability and integrity of the spike protein. The results suggest that the D614G mutant may employ a hinge-shift mechanism in which the dynamic couplings between the site of mutation and the interprotomer hinge modulate the interdomain interactions, global mobility change, and the increased stability of the open form. This study proposes that mutation-induced modulation of the conformational flexibility and energetic frustration at the interprotomer interfaces may serve as an efficient mechanism for allosteric regulation of the SARS-CoV-2 spike proteins.

Identification of a Potential mRNA-based Vaccine Candidate against the SARS-CoV-2 Spike Glycoprotein: A Reverse Vaccinology Approach

The emergence of the novel coronavirus (SARS-CoV-2) in December 2019 has generated a devastating global consequence which makes the development of a rapidly deployable, effective and safe vaccine candidate an imminent global health priority. The design of most vaccine candidates has been directed at the induction of antibody responses against the trimeric spike glycoprotein of SARS-CoV-2, a class I fusion protein that aids ACE2 (angiotensin-converting enzyme 2) receptor binding. A variety of formulations and vaccinology approaches are being pursued for targeting the spike glycoprotein, including simian and human replication-defective adenoviral vaccines, subunit protein vaccines, nucleic acid vaccines and whole-inactivated SARS-CoV-2. Here, we directed a reverse vaccinology approach towards the design of a nucleic acid (mRNA-based) vaccine candidate. The "YLQPRTFLL" peptide sequence (position 269-277) which was predicted to be a B cell epitope and likewise a strong binder of the HLA*A-0201 was selected for the design of the vaccine candidate, having satisfied series of antigenicity assessments. Through the codon optimization protocol, the nucleotide sequence for the vaccine candidate design was generated and targeted at the human toll-like receptor 7 (TLR7). Bioinformatics analyses showed that the sequence "UACCUGCAGCCGCGUACCUUCCUGCUG" exhibited a strong affinity and likewise was bound to a stable cavity in the TLR7 pocket. This study is therefore expected to contribute to the research efforts directed at securing definitive preventive measures against the SARS-CoV-2 infection.

Allosteric Determinants of the SARS-CoV-2 Spike Protein Binding with Nanobodies: Examining Mechanisms of Mutational Escape and Sensitivity of the Omicron Variant

Structural and biochemical studies have recently revealed a range of rationally engineered nanobodies with efficient neutralizing capacity against the SARS-CoV-2 virus and resilience against mutational escape. In this study, we performed a comprehensive computational analysis of the SARS-CoV-2 spike trimer complexes with single nanobodies Nb6, VHH E, and complex with VHH E/VHH V nanobody combination. We combined coarse-grained and all-atom molecular simulations and collective dynamics analysis with binding free energy scanning, perturbation-response scanning, and network centrality analysis to examine mechanisms of nanobody-induced allosteric modulation and cooperativity in the SARS-CoV-2 spike trimer complexes with these nanobodies. By quantifying energetic and allosteric determinants of the SARS-CoV-2 spike protein binding with nanobodies, we also examined nanobody-induced modulation of escaping mutations and the effect of the Omicron variant on nanobody binding. The mutational scanning analysis supported the notion that E484A mutation can have a significant detrimental effect on nanobody binding and result in Omicron-induced escape from nanobody neutralization. Our findings showed that SARS-CoV-2 spike protein might exploit the plasticity of specific allosteric hotspots to generate escape mutants that alter response to binding without compromising activity. The network analysis supported these findings showing that VHH E/VHH V nanobody binding can induce long-range couplings between the cryptic binding epitope and ACE2-binding site through a broader ensemble of communication paths that is less dependent on specific mediating centers and therefore may be less sensitive to mutational perturbations of functional residues. The results suggest that binding affinity and long-range communications of the SARS-CoV-2 complexes with nanobodies can be determined by structurally stable regulatory centers and conformationally adaptable hotspots that are allosterically coupled and collectively control resilience to mutational escape.

Conformational Flexibility and Local Frustration in the Functional States of the SARS-CoV-2 Spike B.1.1.7 and B.1.351 Variants: Mutation-Induced Allosteric Modulation Mechanism of Functional Dynamics and Protein Stability

Structural and functional studies of the SARS-CoV-2 spike proteins have recently determined distinct functional states of the B.1.1.7 and B.1.351 spike variants, providing a molecular framework for understanding the mechanisms that link the effect of mutations with the enhanced virus infectivity and transmissibility. A detailed dynamic and energetic analysis of these variants was undertaken in the present work to quantify the effects of different mutations on functional conformational changes and stability of the SARS-CoV-2 spike protein. We employed the efficient and accurate coarse-grained (CG) simulations of multiple functional states of the D614G mutant, B.1.1.7 and B.1.351 spike variants to characterize conformational dynamics of the SARS-CoV-2 spike proteins and identify dynamic signatures of the functional regions that regulate transitions between the closed and open forms. By combining molecular simulations with full atomistic reconstruction of the trajectories and the ensemble-based mutational frustration analysis, we characterized how the intrinsic flexibility of specific spike regions can control functional conformational changes required for binding with the host-cell receptor. Using the residue-based mutational scanning of protein stability, we determined protein stability hotspots and identified potential energetic drivers favoring the receptor-accessible open spike states for the B.1.1.7 and B.1.351 spike variants. The results suggested that modulation of the energetic frustration at the inter-protomer interfaces can serve as a mechanism for allosteric couplings between mutational sites and the inter-protomer hinges of functional motions. The proposed mechanism of mutation-induced energetic frustration may result in greater adaptability and the emergence of multiple conformational states in the open form. This study suggested that SARS-CoV-2 B.1.1.7 and B.1.351 variants may leverage the intrinsic plasticity of functional regions in the spike protein for mutation-induced modulation of protein dynamics and allosteric regulation to control binding with the host cell receptor.

Computational Models for the Study of Protein Aggregation

Protein aggregation has been studied by many groups around the world for many years because it can be the cause of a number of neurodegenerative diseases that have no effective treatment. Obtaining the structure of related fibrils and toxic oligomers, as well as describing the pathways and main factors that govern the self-organization process, is of paramount importance, but it is also very difficult. To solve this problem, experimental and computational methods are often combined to get the most out of each method. The effectiveness of the computational approach largely depends on the construction of a reasonable molecular model. Here we discussed different versions of the four most popular all-atom force fields AMBER, CHARMM, GROMOS, and OPLS, which have been developed for folded and intrinsically disordered proteins, or both. Continuous and discrete coarse-grained models, which were mainly used to study the kinetics of aggregation, are also summarized.

β-Carboline alkaloids induce structural plasticity and inhibition of SARS-CoV-2 nsp3 macrodomain more potently than remdesivir metabolite GS-441524: computational approach

The nsp3 macrodomain is implicated in the viral replication, pathogenesis and host immune responses through the removal of ADP-ribosylation sites during infections of coronaviruses including the SARS-CoV-2. It has ever been modulated by macromolecules including the ADP-ribose until Ni and co-workers recently reported its inhibition and plasticity enhancement unprecedentedly by remdesivir metabolite, GS-441524, creating an opportunity for investigating other biodiverse small molecules such as β-Carboline (βC) alkaloids. In this study, 1497 βC analogues from the HiT2LEAD chemical database were screened, using computational approaches of Glide XP docking, molecular dynamics simulation and pk-CSM ADMET predictions. Selectively, βC ligands, 129, 584, 1303 and 1323 demonstrated higher binding affinities to the receptor, indicated by XP docking scores of -10.72, -10.01, -9.63 and -9.48 kcal/mol respectively than remdesivir and GS-441524 with -4.68 and -9.41 kcal/mol respectively. Consistently, their binding free energies were -36.07, -23.77, -24.07 and -17.76 kcal/mol respectively, while remdesivir and GS-441524 showed -21.22 and -24.20 kcal/mol respectively. Interestingly, the selected βC ligands displayed better stability and flexibility for enhancing the plasticity of the receptor than GS-441524, especially 129 and 1303. Their predicted ADMET parameters favour druggability and low expressions for toxicity. Thus, they are recommended as promising adjuvant/standalone anti-SARS-CoV-2 candidates for further study.Key words: SARS-CoV-2, nsp3 macrodomain, ADP-ribose, β-carboline, bioinformatics, drug design.

Protein-Protein Docking with Large-Scale Backbone Flexibility Using Coarse-Grained Monte-Carlo Simulations

Most of the protein–protein docking methods treat proteins as almost rigid objects. Only the side-chains flexibility is usually taken into account. The few approaches enabling docking with a flexible backbone typically work in two steps, in which the search for protein–protein orientations and structure flexibility are simulated separately. In this work, we propose a new straightforward approach for docking sampling. It consists of a single simulation step during which a protein undergoes large-scale backbone rearrangements, rotations, and translations. Simultaneously, the other protein exhibits small backbone fluctuations. Such extensive sampling was possible using the CABS coarse-grained protein model and Replica Exchange Monte Carlo dynamics at a reasonable computational cost. In our proof-of-concept simulations of 62 protein–protein complexes, we obtained acceptable quality models for a significant number of cases.

Biomolecular response to hour-long ultralow field microwave radiation: An effective coarse-grained model simulation

Various electronic devices, which we commonly use, radiate microwaves. Such external perturbation influences the functionality of biomolecules. In an ultralow field, the cumulative response of a molecule is expected only over a time scale of hours. To study the structural dynamics of biomolecules over hours, we adopt a simple methodology for constructing the coarse-grained structure of the protein molecule and solve the Langevin equation under different working potentials. In this approach, each amino acid residue of a biomolecule is mapped onto a number of beads, a few for the backbone, and few for the side chain, depending on the complexity of its chemical structure. We choose the force field in such a way that the dynamics of the protein molecule in the presence of ultralow radiation field of microvolt/nm could be followed over the time frame of 2 h. We apply the model to describe a biomolecule, hen egg white lysozyme, and simulate its structural evolution under ultralow strength electromagnetic radiation. The simulation revealed the finer structural details, like the extent of exposure of bioactive residues and the state of the secondary structures of the molecule, further confirmed from spectroscopic measurements [details are available in Phys. Rev. E 97, 052416 (2018)10.1103/PhysRevE.97.052416 and briefly described here]. Though tested for a specific system, the model is quite general. We believe that it harnesses the potential in studying the structural dynamics of any biopolymer under external perturbation over an extended time scale.

Protocols for Fast Simulations of Protein Structure Flexibility Using CABS-Flex and SURPASS

Conformational flexibility of protein structures can play an important role in protein function. The flexibility is often studied using computational methods since experimental characterization can be difficult. Depending on protein system size, computational tools may require large computational resources or significant simplifications in the modeled systems to speed up calculations. In this work, we present the protocols for efficient simulations of flexibility of folded protein structures that use coarse-grained simulation tools of different resolutions: medium, represented by CABS-flex, and low, represented by SUPRASS. We test the protocols using a set of 140 globular proteins and compare the results with structure fluctuations observed in MD simulations, ENM modeling, and NMR ensembles. As demonstrated, CABS-flex predictions show high correlation to experimental and MD simulation data, while SURPASS is less accurate but promising in terms of future developments.

Web-based tools for computational enzyme design

Enzymes are in high demand for very diverse biotechnological applications. However, natural biocatalysts often need to be engineered for fine-tuning their properties towards the end applications, such as the activity, selectivity, stability to temperature or co-solvents, and solubility. Computational methods are increasingly used in this task, providing predictions that narrow down the space of possible mutations significantly and can enormously reduce the experimental burden. Many computational tools are available as web-based platforms, making them accessible to non-expert users. These platforms are typically user-friendly, contain walk-throughs, and do not require deep expertise and installations. Here we describe some of the most recent outstanding web-tools for enzyme engineering and formulate future perspectives in this field.

Exploring the active constituents of Oroxylum indicum in intervention of novel coronavirus (COVID-19) based on molecular docking method

The severe acute respiratory syndrome COVID-19 declared a global pandemic by WHO has become the present wellbeing worry to the whole world. There is an emergent need to search for possible medications. We report in this study a molecular docking study of eighteen Oroxylum indicum molecules with the main protease (Mpro) responsible for the replication of SARS-CoV-2 virus. The outcome of their molecular simulation and ADMET properties reveal four potential inhibitors of the enzyme (Baicalein-7-O-diglucoside, Chrysin-7-O-glucuronide, Oroxindin and Scutellarein) with preference of ligand Chrysin-7-O-glucuronide that has the second highest binding energy (- 8.6 kcal/mol) and fully obeys the Lipinski's rule of five.

SUPPLEMENTARY INFORMATION

The online version contains supplementary material available at 10.1007/s13721-020-00279-y.

Functional characterization of two type-1 diacylglycerol acyltransferase (DGAT1) genes from rice (Oryza sativa) embryo restoring the triacylglycerol accumulation in yeast

Two OsDGAT1 genes showed the ability to restore TAG and LB synthesis in yeast H1246. Alterations in the N-terminal region of OsDGAT1-1 gene revealed its regulatory role in gene function. Accumulation of triacylglycerol (TAG) or oil in vegetative tissues has emerged as a promising approach to meet the global needs of food, feed, and fuel. Rice (Oryza sativa) has been recognized as an important cereal crop containing nutritional rice bran oil with high economic value for renewable energy production. To identify the key component involved in storage lipid biosynthesis, two type-1 diacylglycerol acyltransferases (DGAT1) from rice were characterized for its in vivo function in the H1246 (dga1, lro1, are1 and are2) yeast quadruple mutant. The ectopic expression of rice DGAT1 (designated as OsDGAT1-1 and OsDGAT1-2) genes restored the capability of TAG synthesis and lipid body (LB) formation in H1246. OsDGAT1-1 showed nearly equal substrate preferences to C16:0-CoA and 18:1-CoA whereas OsDGAT1-2 displayed substrate selectivity for C16:0-CoA over 18:1-CoA, indicating that these enzymes have contrasting substrate specificities. In parallel, we have identified the intrinsically disordered region (IDR) at the N-terminal domains of OsDGAT1 proteins. The regulatory role of the N-terminal domain was dissected. Single point mutations at the phosphorylation sites and truncations of the N-terminal region highlighted reduced lipid accumulation capabilities among different OsDGAT1-1 variants.

Dynamic Network Modeling of Allosteric Interactions and Communication Pathways in the SARS-CoV-2 Spike Trimer Mutants: Differential Modulation of Conformational Landscapes and Signal Transmission via Cascades of Regulatory Switches

The rapidly growing body of structural and biochemical studies of the SARS-CoV-2 spike glycoprotein has revealed a variety of distinct functional states with radically different arrangements of the receptor-binding domain, highlighting a remarkable function-driven conformational plasticity and adaptability of the spike proteins. In this study, we examined molecular mechanisms underlying conformational and dynamic changes in the SARS-CoV-2 spike mutant trimers through the lens of dynamic analysis of allosteric interaction networks and atomistic modeling of signal transmission. Using an integrated approach that combined coarse-grained molecular simulations, protein stability analysis, and perturbation-based modeling of residue interaction networks, we examined how mutations in the regulatory regions of the SARS-CoV-2 spike protein can differentially affect dynamics and allosteric signaling in distinct functional states. The results of this study revealed key functional regions and regulatory centers that govern collective dynamics, allosteric interactions, and control signal transmission in the SARS-CoV-2 spike proteins. We found that the experimentally confirmed regulatory hotspots that dictate dynamic switching between conformational states of the SARS-CoV-2 spike protein correspond to the key hinge sites and global mediating centers of the allosteric interaction networks. The results of this study provide a novel insight into allosteric regulatory mechanisms of SARS-CoV-2 spike proteins showing that mutations at the key regulatory positions can differentially modulate distribution of states and determine topography of signal communication pathways operating through state-specific cascades of control switch points. This analysis provides a plausible strategy for allosteric probing of the conformational equilibrium and therapeutic intervention by targeting specific hotspots of allosteric interactions and communications in the SARS-CoV-2 spike proteins.

Molecular Cloning, Purification and Characterization of Mce1R of Mycobacterium tuberculosis

The mce1 operon of Mycobacterium tuberculosis, important for lipid metabolism/transport, host cell invasion, modulation of host immune response and pathogenicity, is under the transcriptional control of Mce1R. Hence characterizing Mce1R is an important step for novel anti-tuberculosis drug discovery. The present study reports functional and in silico characterization of Mce1R. In this work, we have computationally modeled the structure of Mce1R and have validated the structure by computational and experimental methods. Mce1R has been shown to harbor the canonical VanR-like structure with a flexible N-terminal 'arm', carrying conserved positively charged residues, most likely involved in the operator DNA binding. The mce1R gene has been cloned, expressed, purified and its DNA-binding activity has been measured in vitro. The K_d value for Mce1R-operator DNA interaction has been determined to be 0.35 ± 0.02 µM which implies that Mce1R binds to DNA with moderate affinity compared to the other FCD family of regulators. So far, this is the first report for measuring the DNA-binding affinity of any VanR-type protein. Despite significant sequence similarity at the N-terminal domain, the wHTH motif of Mce1R exhibits poor conservancy of amino acid residues, critical for DNA-binding, thus results in moderate DNA-binding affinity. The N-terminal DNA-binding domain is structurally dynamic while the C-terminal domain showed significant stability and such profile of structural dynamics is most likely to be preserved in the structural orthologs of Mce1R. In addition to this, a cavity has been detected in the C-terminal domain of Mce1R which contains a few conserved residues. Comparison with other FCD family of regulators suggests that most of the conserved residues might be critical for binding to specific ligand. The max pKd value and drug score for the cavity are estimated to be 9.04 and 109 respectively suggesting that the cavity represents a suitable target site for novel anti-tuberculosis drug discovery approaches.

Identification of Potential Flavonoid Inhibitors of the SARS-CoV-2 Main Protease 6YNQ: A Molecular Docking Study

Objective

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the causative agent for coronavirus disease 2019 (COVID-19), is responsible for the recent global pandemic. As there are no effective drugs or vaccines available for SARS-CoV-2, we investigated the potential of flavonoids against SARS-CoV-2 main protease 6YNQ.

Methods

In silico molecular simulation study against SARS-CoV-2 main protease 6YNQ.

Results

Among the 21 selected flavonoids, rutin demonstrated the highest binding energy (− 8.7 kcal/mol) and displayed perfect binding with the catalytic sites.

Conclusions

Our study demonstrates the inhibitory potential of flavonoids against SARS-CoV-2 main protease 6YNQ. These computational simulation studies support the hypothesis that flavonoids might be helpful for the treatment of COVID-19.

Design and development of a chimeric vaccine candidate against zoonotic hepatitis E and foot-and-mouth disease

Background

Zoonotic hepatitis E virus (HEV) infection emerged as a serious threat in the industrialized countries. The aim of this study is exploring a new approach for the control of zoonotic HEV in its main host (swine) through the design and development of an economically interesting chimeric vaccine against HEV and against a devastating swine infection: the foot-and-mouth disease virus (FMDV) infection.

Results

First, we adopted a computational approach for rational and effective screening of the different HEV-FMDV chimeric proteins. Next, we further expressed and purified the selected chimeric immunogens in Escherichia coli (E. coli) using molecular cloning techniques. Finally, we assessed the antigenicity and immunogenicity profiles of the chimeric vaccine candidates. Following this methodology, we designed and successfully produced an HEV-FMDV chimeric vaccine candidate (Seq 8-P222) that was highly over-expressed in E. coli as a soluble protein and could self-assemble into virus-like particles. Moreover, the vaccine candidate was thermo-stable and exhibited optimal antigenicity and immunogenicity properties.

Conclusion

This study provides new insights into the vaccine development technology by using bioinformatics for the selection of the best candidates from larger sets prior to experimentation. It also presents the first HEV-FMDV chimeric protein produced in E. coli as a promising chimeric vaccine candidate that could participate in reducing the transmission of zoonotic HEV to humans while preventing the highly contagious foot-and-mouth disease in swine.

Artificial iron hydrogenase made by covalent grafting of Knölker's complex into xylanase: Application in asymmetric hydrogenation of an aryl ketone in water

We report a new artificial hydrogenase made by covalent anchoring of the iron Knölker's complex to a xylanase S212C variant. This artificial metalloenzyme was found to be able to catalyze efficiently the transfer hydrogenation of the benchmark substrate trifluoroacetophenone by sodium formate in water, yielding the corresponding secondary alcohol as a racemic. The reaction proceeded more than threefold faster with the XlnS212CK biohybrid than with the Knölker's complex alone. In addition, efficient conversion of trifluoroacetophenone to its corresponding alcohol was reached within 60 H with XlnS212CK, whereas a ≈2.5-fold lower conversion was observed with Knölker's complex alone as catalyst. Moreover, the data were rationalized with a computational strategy suggesting the key factors of the selectivity. These results suggested that the Knölker's complex was most likely flexible and could experience free rotational reorientation within the active-site pocket of Xln A, allowing it to access the subsite pocket populated by trifluoroacetophenone.

Aggrescan3D (A3D) 2.0: prediction and engineering of protein solubility

Protein aggregation is a hallmark of a growing number of human disorders and constitutes a major bottleneck in the manufacturing of therapeutic proteins. Therefore, there is a strong need of in-silico methods that can anticipate the aggregative properties of protein variants linked to disease and assist the engineering of soluble protein-based drugs. A few years ago, we developed a method for structure-based prediction of aggregation properties that takes into account the dynamic fluctuations of proteins. The method has been made available as the Aggrescan3D (A3D) web server and applied in numerous studies of protein structure-aggregation relationship. Here, we present a major update of the A3D web server to version 2.0. The new features include: extension of dynamic calculations to significantly larger and multimeric proteins, simultaneous prediction of changes in protein solubility and stability upon mutation, rapid screening for functional protein variants with improved solubility, a REST-ful service to incorporate A3D calculations in automatic pipelines, and a new, enhanced web server interface. A3D 2.0 is freely available at: http://biocomp.chem.uw.edu.pl/A3D2/

Flexible docking of peptides to proteins using CABS-dock

Molecular docking of peptides to proteins can be a useful tool in the exploration of the possible peptide binding sites and poses. CABS-dock is a method for protein-peptide docking that features significant conformational flexibility of both the peptide and the protein molecules during the peptide search for a binding site. The CABS-dock has been made available as a web server and a standalone package. The web server is an easy to use tool with a simple web interface. The standalone package is a command-line program dedicated to professional users. It offers a number of advanced features, analysis tools and support for large-sized systems. In this article, we outline the current status of the CABS-dock method, its recent developments, applications, and challenges ahead.

CABS-flex 2.0: a web server for fast simulations of flexibility of protein structures

Classical simulations of protein flexibility remain computationally expensive, especially for large proteins. A few years ago, we developed a fast method for predicting protein structure fluctuations that uses a single protein model as the input. The method has been made available as the CABS-flex web server and applied in numerous studies of protein structure-function relationships. Here, we present a major update of the CABS-flex web server to version 2.0. The new features include: extension of the method to significantly larger and multimeric proteins, customizable distance restraints and simulation parameters, contact maps and a new, enhanced web server interface. CABS-flex 2.0 is freely available at http://biocomp.chem.uw.edu.pl/CABSflex2.

Prediction and characterisation of lantibiotic structures with molecular modelling and molecular dynamics simulations

Lantibiotics are lanthionine-containing bactericidal peptides produced by gram-positive bacteria as a defence mechanism against other bacterial species. Lantipeptides disrupt the integrity of target cells by forming pores in their cell membranes, or by preventing cell wall biosynthesis, which subsequently results in cell death. Lantibiotics are of immense importance to the food preservation and pharmaceutical industries. The rise in multidrug resistance demands the discovery of novel antimicrobials, and several authors advocate that lantibiotics hold the future of antimicrobial drug discovery. Owing to their amenability to structural modifications, novel lantibiotics with higher efficacy and antimicrobial activity can be constructed by bioengineering and nanoengineering strategies, and is opined to have immense therapeutic success in combating the rise in multidrug resistance. Understanding the structure and dynamics of lantibiotics is therefore crucial for the development of novel lantipeptides, and this study aimed to study the structural properties and dynamics of 37 lantibiotics using computational strategies. The structures of these 37 lantibiotics were constructed from homology, and their structural stability and compactness were analysed by molecular dynamics simulations. The phylogenetic relationships, physicochemical properties, disordered regions, pockets, intramolecular bonds and interactions, and structural diversity of the 37 lantipeptides were studied. The structures of the 37 lantipeptides constructed herein remained stable throughout simulation. The study revealed that the structural diversity of lantibiotics is not significantly correlated to sequence diversity, and this property could be exploited for designing novel lantipeptides with higher efficacy.

CABS-flex standalone: a simulation environment for fast modeling of protein flexibility

SUMMARY

CABS-flex standalone is a Python package for fast simulations of protein structure flexibility. The package combines simulations of protein dynamics using CABS coarse-grained protein model with the reconstruction of selected models to all-atom representation and analysis of modeling results. CABS-flex standalone is designed to allow for command-line access to the CABS computations and complete control over simulation process. CABS-flex standalone is equipped with features such as: modeling of multimeric and large-size protein systems, contact map visualizations, analysis of similarities to the reference structure and configurable modeling protocol. For instance, the user may modify the simulation parameters, distance restraints, structural clustering scheme or all-atom reconstruction parameters. With these features CABS-flex standalone can be easily incorporated into other methodologies of structural biology.

AVAILABILITY AND IMPLEMENTATION

CABS-flex standalone is distributed under the MIT license, which is free for academic and non-profit users. It is implemented in Python. CABS-flex source code, wiki with examples of use and installation instructions for Linux, macOS and Windows are available from the CABS-flex standalone repository at https://bitbucket.org/lcbio/cabsflex.

Modeling of Disordered Protein Structures Using Monte Carlo Simulations and Knowledge-Based Statistical Force Fields

The description of protein disordered states is important for understanding protein folding mechanisms and their functions. In this short review, we briefly describe a simulation approach to modeling protein interactions, which involve disordered peptide partners or intrinsically disordered protein regions, and unfolded states of globular proteins. It is based on the CABS coarse-grained protein model that uses a Monte Carlo (MC) sampling scheme and a knowledge-based statistical force field. We review several case studies showing that description of protein disordered states resulting from CABS simulations is consistent with experimental data. The case studies comprise investigations of protein⁻peptide binding and protein folding processes. The CABS model has been recently made available as the simulation engine of multiscale modeling tools enabling studies of protein⁻peptide docking and protein flexibility. Those tools offer customization of the modeling process, driving the conformational search using distance restraints, reconstruction of selected models to all-atom resolution, and simulation of large protein systems in a reasonable computational time. Therefore, CABS can be combined in integrative modeling pipelines incorporating experimental data and other modeling tools of various resolution.

Computational characterization and molecular dynamics simulation of the thermostable direct hemolysin-related hemolysin (TRH) amplified from Vibrio parahaemolyticus

Vibrio parahaemolyticus is a major seafood-borne pathogen that causes life-threatening gastroenteric diseases in humans through the consumption of contaminated seafoods. V. parahaemolyticus produces different kinds of toxins, including thermostable direct hemolysin (TDH), TDH-related hemolysin (TRH), and some effector proteins belonging to the Type 3 Secretion System, out of which TDH and TRH are considered to be the major factors for virulence. Although TRH is one of the major virulent proteins, there is a dearth of understanding about the structural and functional properties of this protein. This study therefore aimed to amplify the full length trh gene from V. parahaemolyticus and perform sequence-based analyses, followed by structural and functional analyses of the TRH protein using different bioinformatics tools. The TRH protein shares significant conservedness with the TDH protein. A multiple sequence alignment of TRH proteins from Vibrio and non-Vibrio species revealed that the TRH protein is highly conserved throughout evolution. The three dimensional (3D) structure of the TRH protein was constructed by comparative modelling and the quality of the predicted model was verified. Molecular dynamics simulations were performed to understand the dynamics, residual fluctuations, and the compactness of the protein. The structure of TRH was found to contain 19 pockets, of which one (pocket ID: 2) was predicted to be important from the view of drug design. Eleven residues (E138, Y140, C151, F158, C161, K162, S163, and Q164), which are reported to actively participate in the formation of the tetrameric structure, were present in this pocket. This study extends our understanding of the structural and functional dynamics of the TRH protein and as well as provides new insights for the treatment and prevention of V. parahaemolyticus infections.

Modeling of Protein Structural Flexibility and Large-Scale Dynamics: Coarse-Grained Simulations and Elastic Network Models

Fluctuations of protein three-dimensional structures and large-scale conformational transitions are crucial for the biological function of proteins and their complexes. Experimental studies of such phenomena remain very challenging and therefore molecular modeling can be a good alternative or a valuable supporting tool for the investigation of large molecular systems and long-time events. In this minireview, we present two alternative approaches to the coarse-grained (CG) modeling of dynamic properties of protein systems. We discuss two CG representations of polypeptide chains used for Monte Carlo dynamics simulations of protein local dynamics and conformational transitions, and highly simplified structure-based elastic network models of protein flexibility. In contrast to classical all-atom molecular dynamics, the modeling strategies discussed here allow the quite accurate modeling of much larger systems and longer-time dynamic phenomena. We briefly describe the main features of these models and outline some of their applications, including modeling of near-native structure fluctuations, sampling of large regions of the protein conformational space, or possible support for the structure prediction of large proteins and their complexes.