Is an intuitive convergence definition of molecular dynamics simulations solely based on the root mean square deviation possible?

Expression analysis and mapping of Viral-Host Protein interactions of Poxviridae suggests a lead candidate molecule targeting Mpox

BACKGROUND

Monkeypox (Mpox) is an important human pathogen without etiological treatment. A viral-host interactome study may advance our understanding of molecular pathogenesis and lead to the discovery of suitable therapeutic targets.

METHODS

GEO Expression datasets characterizing mRNA profile changes in different host responses to poxviruses were analyzed for shared pathway identification, and then, the Protein-protein interaction (PPI) maps were built. The viral gene expression datasets of Monkeypox virus (MPXV) and Vaccinia virus (VACV) were used to identify the significant viral genes and further investigated for their binding to the library of targeting molecules.

RESULTS

Infection with MPXV interferes with various cellular pathways, including interleukin and MAPK signaling. While most host differentially expressed genes (DEGs) are predominantly downregulated upon infection, marked enrichments in histone modifiers and immune-related genes were observed. PPI analysis revealed a set of novel virus-specific protein interactions for the genes in the above functional clusters. The viral DEGs exhibited variable expression patterns in three studied cell types: primary human monocytes, primary human fibroblast, and HeLa, resulting in 118 commonly deregulated proteins. Poxvirus proteins C6R derived protein K7 and K7R of MPXV and VACV were prioritized as targets for potential therapeutic interventions based on their histone-regulating and immunosuppressive properties. In the computational docking and Molecular Dynamics (MD) experiments, these proteins were shown to bind the candidate small molecule S3I-201, which was further prioritized for lead development.

RESULTS

MPXV circumvents cellular antiviral defenses by engaging histone modification and immune evasion strategies. C6R-derived protein K7 binding candidate molecule S3I-201 is a priority promising candidate for treating Mpox.

In silico and in vitro assays suggests Congo red dye degradation by a Lentinus sp. laccase enzyme

Laccase is a superfamily of ligninolytic enzymes known to degrade a wide variety of xenobiotics, including synthetic dyes. Congo Red (CR) has a diazo dye function, carcinogenic and mutagenic potential, and is currently applied in clinical analysis. The objective of this work was to produce and characterize the crude extract of Lentinus sp. in semi-solid fermentation (FSS) and perform in vitro and in silico studies to assess the potential of the crude extract to discolor the CR dye. Laccase activity was determined using ABTS as substrate and characterized. The in vitro discoloration was carried out using experimental design 22 at room temperature and monitored at 340 nm for 24h. Molecular docking and molecular dynamics simulations were performed between laccase and CR. The maximum laccase activity production was 29.63 U L-1 with six days of FSS. The optimal temperature and pH were 50 °C and 3.0, respectively. Discoloration of the CR dye was obtained only in tests containing CuSO4. Laccase formed stable complexes with the dye, presenting negative binding energy values ranging from -70.94 to -63.16 kcal mol-1 and the occurrence of seven hydrogen bonds. Molecular dynamics results showed the stability of the system (RMSD ranging from 1.0 to 2.5 Ä) and protein-ligand interaction along simulation. RMSF values pointed residues at the end of chains A (residues 300 to 305, 480 to 500) and B (residues 650 to 655 and 950 to 1000) as the most flexible regions of the laccase. This study highlighted the enzymatic action in the bioremediation of CR in vitro in agreement with the in silico simulations that demonstrate the enzyme potential.Communicated by Ramaswamy H. Sarma.

Variant of uncertain significance Arg866Cys enhances disorderedness of h-BRCA1 (759-1064) region

High structural flexibility has been reported in the central region of BRCA1, which hinders the structural and functional evaluations of mutations identified in the domain. Additionally, the need to categorize variants of unknown significance (VUS) has increased due to the growth in the number of variants reported in clinical settings. Therefore, unraveling the disease-causing mechanism of VUS identified in different functional domains of BRCA1 is still challenging. The current study uses a multidisciplinary approach to assess the structural impact of BRCA1 Arg866Cys mutation discovered in the central domain of BRCA1. The structural alterations have been characterized using Circular-Dichroism spectroscopy, nano-DSF, and molecular-dynamics simulations. BRCA1 Arg866Cys mutant demonstrated more flexibility and lesser affinity to DNA than the wild-type protein. The BRCA1(759-1064) wild-type protein was shown to be a βII-rich protein with an induced D-O transition in the presence of DNA and 2,2,2-Trifluoroethanol (TFE). The protein's alpha-helical composition did not significantly change in the presence of TFE, besides an increase in β-turns and loops. Under Transmission Electron Microscopes (TEM), amyloid-like fibrils structure was detected for Arg866Cys mutant whereas the wild-type protein showed amorphous aggregates. An increased ThT fluorescence indicated β-rich composition and aggregation-prone behaviour for BRCA1 wild-type protein, while the fluorescence intensity was significantly quenched in the Arg866Cys mutant. Furthermore, increased conformational flexibility in the Arg866Cys variant was observed by principal component analysis. This work aims to comprehend the inherently disordered region of BRCA1 as well as the impact of missense mutations on folding patterns and binding to DNA for functional aspects.

In silico analysis of alpha-synuclein protein variants and posttranslational modifications related to Parkinson's disease

Parkinson's disease (PD) is among the most prevalent neurodegenerative disorders, affecting over 10 million people worldwide. The protein encoded by the SNCA gene, alpha-synuclein (ASYN), is the major component of Lewy body (LB) aggregates, a histopathological hallmark of PD. Mutations and posttranslational modifications (PTMs) in ASYN are known to influence protein aggregation and LB formation, possibly playing a crucial role in PD pathogenesis. In this work, we applied computational methods to characterize the effects of missense mutations and PTMs on the structure and function of ASYN. Missense mutations in ASYN were compiled from the literature/databases and underwent a comprehensive predictive analysis. Phosphorylation and SUMOylation sites of ASYN were retrieved from databases and predicted by algorithms. ConSurf was used to estimate the evolutionary conservation of ASYN amino acids. Molecular dynamics (MD) simulations of ASYN wild-type and variants A30G, A30P, A53T, and G51D were performed using the GROMACS package. Seventy-seven missense mutations in ASYN were compiled. Although most mutations were not predicted to affect ASYN stability, aggregation propensity, amyloid formation, and chaperone binding, the analyzed mutations received relatively high rates of deleterious predictions and predominantly occurred at evolutionarily conserved sites within the protein. Moreover, our predictive analyses suggested that the following mutations may be possibly harmful to ASYN and, consequently, potential targets for future investigation: K6N, T22I, K34E, G36R, G36S, V37F, L38P, G41D, and K102E. The MD analyses pointed to remarkable flexibility and essential dynamics alterations at nearly all domains of the studied variants, which could lead to impaired contact between NAC and the C-terminal domain triggering protein aggregation. These alterations may have functional implications for ASYN and provide important insight into the molecular mechanism of PD, supporting the design of future biomedical research and improvements in existing therapies for the disease.

Identification of coastal pesticide pollutants as potent inhibitors of Bacillus pasteurii urease mediated calcium carbonate precipitation: a computational approach

Microbially induced calcite precipitation (MICP) through urease enzyme has attained a lot of recognition in various fields of civil engineering and geotechnology for stabilizing the strength of soil and various concrete materials. The activity of urease has been found to be affected by various factors like temperature, substrate concentrations, pH of the medium, presence of inhibitors, etc. Through this study, the outcome of the interaction of pesticides (commonly found in Indian coastal regions) on Bacillus pasteurii urease, a major organism reported for MICP studies has been investigated in silico. The results from the study revealed that the enzyme has higher interactions of -4.1, -3.2, and -3.4 kJ/mol with common pesticides like dichloro diphenyl dichloro ethane(DDD), dichloro diphenyl trichloroe thane (DDT), and methyl parathion of organochlorides and organophosphates class. From the molecular dynamics simulation analysis, complex 1 (DDD -receptor) has been found to have the highest and more compact structure followed by methyl parathion -receptor. Prime MM-GBSA analysis also revealed the highest binding energy of -27.8 kcal/mol with the protein and DDD. Thus, it can be inferred from the current study that pesticides, particularly, DDD, DDT, and methyl parathion present in the coastal areas may have an impact on urease. This interaction can result in the inhibition of the urease activity of B. pasteurii, thus preventing the biomineralization process. This study would be the first report on the computational approach to understanding the interaction of prominent pesticides on the coastal region and B. pasteurii urease.Communicated by Ramaswamy H. Sarma.

Dynamozones are the most obvious sign of the evolution of conformational dynamics in HIV-1 protease

Proteins are not static but are flexible molecules that can adopt many different conformations. The HIV-1 protease is an important target for the development of therapies to treat AIDS, due to its critical role in the viral life cycle. We investigated several dynamics studies on the HIV-1 protease families to illustrate the significance of examining the dynamic behaviors and molecular motions for an entire understanding of their dynamics-structure-function relationships. Using computer simulations and principal component analysis approaches, the dynamics data obtained revealed that: (i) The flap regions are the most obvious sign of the evolution of conformational dynamics in HIV-1 protease; (ii) There are dynamic structural regions in some proteins that contribute to the biological function and allostery of proteins via appropriate flexibility. These regions are a clear sign of the evolution of conformational dynamics of proteins, which we call dynamozones. The flap regions are one of the most important dynamozones members that are critical for HIV-1 protease function. Due to the existence of other members of dynamozones in different proteins, we propose to consider dynamozones as a footprint of the evolution of the conformational dynamics of proteins.

Human soluble CD39 displays substrate inhibition in a substrate-specific manner

CD39 (ectonucleoside triphosphate diphosphohydrolase-1; ENTPD1) metabolizes extracellular ATP and ADP to AMP. AMP is subsequently metabolized by CD79 to adenosine. CD39 activity is therefore a key regulator of purinergic signalling in cancer, thrombosis, and autoimmune diseases. In this study we demonstrate that soluble, recombinant CD39 shows substrate inhibition with ADP or ATP as the substrate. Although CD39 activity initially increased with increasing substrate concentration, at high concentrations of ATP or ADP, CD39 activity was markedly reduced. Although the reaction product, AMP, inhibits CD39 activity, insufficient AMP was generated under our conditions to account for the substrate inhibition seen. In contrast, inhibition was not seen with UDP or UTP as substrates. 2-methylthio-ADP also showed no substrate inhibition, indicating the nucleotide base is an important determinant of substrate inhibition. Molecular dynamics simulations revealed that ADP can undergo conformational rearrangements within the CD39 active site that were not seen with UDP or 2-methylthio-ADP. Appreciating the existence of substrate inhibition of CD39 will help the interpretation of studies of CD39 activity, including investigations into drugs that modulate CD39 activity.

Elucidation of novel compounds and epitope-based peptide vaccine design against C30 endopeptidase regions of SARS-CoV-2 using immunoinformatics approaches

There has been progressive improvement in immunoinformatics approaches for epitope-based peptide design. Computational-based immune-informatics approaches were applied to identify the epitopes of SARS-CoV-2 to develop vaccines. The accessibility of the SARS-CoV-2 protein surface was analyzed, and hexa-peptide sequences (KTPKYK) were observed having a maximum score of 8.254, located between amino acids 97 and 102, whereas the FSVLAC at amino acids 112 to 117 showed the lowest score of 0.114. The surface flexibility of the target protein ranged from 0.864 to 1.099 having amino acid ranges of 159 to 165 and 118 to 124, respectively, harboring the FCYMHHM and YNGSPSG hepta-peptide sequences. The surface flexibility was predicted, and a 0.864 score was observed from amino acids 159 to 165 with the hepta-peptide (FCYMHHM) sequence. Moreover, the highest score of 1.099 was observed between amino acids 118 and 124 against YNGSPSG. B-cell epitopes and cytotoxic T-lymphocyte (CTL) epitopes were also identified against SARS-CoV-2. In molecular docking analyses, -0.54 to -26.21 kcal/mol global energy was observed against the selected CTL epitopes, exhibiting binding solid energies of -3.33 to -26.36 kcal/mol. Based on optimization, eight epitopes (SEDMLNPNY, GSVGFNIDY, LLEDEFTPF, DYDCVSFCY, GTDLEGNFY, QTFSVLACY, TVNVLAWLY, and TANPKTPKY) showed reliable findings. The study calculated the associated HLA alleles with MHC-I and MHC-II and found that MHC-I epitopes had higher population coverage (0.9019% and 0.5639%) than MHC-II epitopes, which ranged from 58.49% to 34.71% in Italy and China, respectively. The CTL epitopes were docked with antigenic sites and analyzed with MHC-I HLA protein. In addition, virtual screening was conducted using the ZINC database library, which contained 3,447 compounds. The 10 top-ranked scrutinized molecules (ZINC222731806, ZINC077293241, ZINC014880001, ZINC003830427, ZINC030731133, ZINC003932831, ZINC003816514, ZINC004245650, ZINC000057255, and ZINC011592639) exhibited the least binding energy (-8.8 to -7.5 kcal/mol). The molecular dynamics (MD) and immune simulation data suggest that these epitopes could be used to design an effective SARS-CoV-2 vaccine in the form of a peptide-based vaccine. Our identified CTL epitopes have the potential to inhibit SARS-CoV-2 replication.

Novel Thiosemicarbazone Quantum Dots in the Treatment of Alzheimer's Disease Combining In Silico Models Using Fingerprints and Physicochemical Descriptors

Searching for thiosemicarbazone derivatives with the potential to inhibit acetylcholinesterase for the treatment of Alzheimer's disease (AD) is an important current goal. The QSAR_KPLS, QSAR_ANN, and QSAR_SVR models were constructed using binary fingerprints and physicochemical (PC) descriptors of 129 thiosemicarbazone compounds screened from a database of 3791 derivatives. The R ² and Q ² values for the QSAR_KPLS, QSAR_ANN, and QSAR_SVR models are greater than 0.925 and 0.713 using dendritic fingerprint (DF) and PC descriptors, respectively. The in vitro pIC₅₀ activities of four new design-oriented compounds N1, N2, N3, and N4, from the QSAR_KPLS model using DFs, are consistent with the experimental results and those from the QSAR_ANN and QSAR_SVR models. The designed compounds N1, N2, N3, and N4 do not violate Lipinski-5 and Veber rules using the ADME and BoiLED-Egg methods. The binding energy, kcal mol^-1, of the novel compounds to the 1ACJ-PDB protein receptor of the AChE enzyme was also obtained by molecular docking and dynamics simulations consistent with those predicted from the QSAR_ANN and QSAR_SVR models. New compounds N1, N2, N3, and N4 were synthesized, and the experimental in vitro pIC₅₀ activity was determined in agreement with those obtained from in silico models. The newly synthesized thiosemicarbazones N1, N2, N3, and N4 can inhibit 1ACJ-PDB, which is predicted to be able to cross the barrier. The DFT B3LYP/def-SV(P)-ECP quantization calculation method was used to calculate E _HOMO and E _LUMO to account for the activities of compounds N1, N2, N3, and N4. The quantum calculation results explained are consistent with those obtained in in silico models. The successful results here may contribute to the search for new drugs for the treatment of AD.

LAST: Latent Space-Assisted Adaptive Sampling for Protein Trajectories

Molecular dynamics (MD) simulation is widely used to study protein conformations and dynamics. However, conventional simulation suffers from being trapped in some local energy minima that are hard to escape. Thus, most of the computational time is spent sampling in the already visited regions. This leads to an inefficient sampling process and further hinders the exploration of protein movements in affordable simulation time. The advancement of deep learning provides new opportunities for protein sampling. Variational autoencoders are a class of deep learning models to learn a low-dimensional representation (referred to as the latent space) that can capture the key features of the input data. Based on this characteristic, we proposed a new adaptive sampling method, latent space-assisted adaptive sampling for protein trajectories (LAST), to accelerate the exploration of protein conformational space. This method comprises cycles of (i) variational autoencoder training, (ii) seed structure selection on the latent space, and (iii) conformational sampling through additional MD simulations. The proposed approach is validated through the sampling of four structures of two protein systems: two metastable states of Escherichia coli adenosine kinase (ADK) and two native states of Vivid (VVD). In all four conformations, seed structures were shown to lie on the boundary of conformation distributions. Moreover, large conformational changes were observed in a shorter simulation time when compared with structural dissimilarity sampling (SDS) and conventional MD (cMD) simulations in both systems. In metastable ADK simulations, LAST explored two transition paths toward two stable states, while SDS explored only one and cMD neither. In VVD light state simulations, LAST was three times faster than cMD simulation with a similar conformational space. Overall, LAST is comparable to SDS and is a promising tool in adaptive sampling. The LAST method is publicly available at https://github.com/smu-tao-group/LAST to facilitate related research.

Potential antiviral peptides targeting the SARS-CoV-2 spike protein

BACKGROUND

The coronavirus disease caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection became an international pandemic and created a public health crisis. The binding of the viral Spike glycoprotein to the human cell receptor angiotensin-converting enzyme 2 (ACE2) initiates viral infection. The development of efficient treatments to combat coronavirus disease is considered essential.

METHODS

An in silico approach was employed to design amino acid peptide inhibitor against the receptor-binding domain (RBD) of the SARS-CoV-2 spike protein. The designed inhibitor (SARS-CoV-2 PEP 49) consists of amino acids with the α1 helix and the β4 - β5 sheets of ACE2. The PEP-FOLD3 web tool was used to create the 3D structures of the peptide amino acids. Analyzing the interaction between ACE2 and the RBD of the Spike protein for three protein data bank entries (6M0J, 7C8D, and 7A95) indicated that the interacting amino acids were contained inside two regions of ACE2: the α1 helical protease domain (PD) and the β4 - β5 sheets.

RESULTS

Molecular docking analysis of the designed inhibitor demonstrated that SARS-CoV-2 PEP 49 attaches directly to the ACE2 binding site of the Spike protein with a binding affinity greater than the ACE2, implying that the SARS-CoV-2 PEP 49 model may be useful as a potential RBD binding blocker.

In-silico discovery of inhibitors against human papillomavirus E1 protein

High-risk (HR) Human papillomavirus (e.g. HPV16 and HPV18) causes approximately two-thirds of all cervical cancers in women. Although the first and second-generation vaccines confer some protection against individuals, there are no approved drugs to treat HR-HPV infections to-date. The HPV E1 protein is an attractive drug target because the protein is highly conserved across all HPV types and is crucial for the regulation of viral DNA replication. Hence, we used the Random Forest algorithm to construct a Quantitative-Structure Activity Relationship (QSAR) model to predict the potential inhibitors against the HPV E1 protein. Our QSAR classification model achieved an accuracy of 87.5%, area under the receiver operating characteristic curve of 1.00, and F-measure of 0.87 when evaluated using an external test set. We conducted a drug repurposing campaign by deploying the model to screen the Drugbank database. The top three compounds, namely Cinalukast, Lobeglitazone, and Efatutazone were analyzed for their cell membrane permeability, toxicity, and carcinogenicity. Finally, these three compounds were subjected to molecular docking and 200 ns-long Molecular Dynamics (MD) simulations. The predicted binding free energies for the candidates were calculated using the MM-GBSA method. The binding free energies for Cinalukast, Lobeglitazone, and Efatutazone were -37.84 kcal/mol, -25.30 kcal/mol, and -29.89 kcal/mol respectively. Therefore, we propose their chemical scaffolds for future rational design of E1 inhibitors.Communicated by Ramaswamy H. Sarma.

Seeking antiviral drugs to inhibit SARS-CoV-2 RNA dependent RNA polymerase: A molecular docking analysis

COVID-19 outbreak associated with the severe acute respiratory syndrome coronavirus (SARS-CoV-2) raised health concerns across the globe and has been considered highly transmissible between people. In attempts for finding therapeutic treatment for the new disease, this work has focused on examining the polymerase inhibitors against the SARS-CoV-2 nsp12 and co-factors nsp8 and nsp7. Several polymerase inhibitors were examined against PDB ID: 6M71 using computational analysis evaluating the ligand's binding affinity to replicating groove to the active site. The findings of this analysis showed Cytarabine of -5.65 Kcal/mol with the highest binding probability (70%) to replicating groove of 6M71. The complex stability was then examined over 19 ns molecular dynamics simulation suggesting that Cytarabine might be possible potent inhibitor for the SARS-CoV-2 RNA Dependent RNA Polymerase.

Prediction of binding affinity of 1,2-diphenyline ketone analogues at adenosine triphosphate binding site of glycogen synthase kinase-3β: a molecular docking and dynamic simulation study

Glycogen synthase kinase (GSK)-3β is one of the downstream signalling molecules involved in phosphorylation of glycogen synthase, a key enzyme involved in the synthesis of glycogen from glucose. GSK-3β regulate some of the critical processes underlying structural and functional synaptic plasticity of neurons. Down regulation or inhibition of GSK-3β enhances long-term potentiation and cognitive functions in animal models of Alzheimer's disease, Parkinson's disease, and amyotrophic lateral sclerosis. A number of compounds are available to inhibit GSK-3β, however none of them are in clinical practice to treat neurodegenerative diseases. The aim of our study was to predict the molecular interaction and dynamic behaviour of naturally occurring 1,2-diphenyline ketone analogues at the adenosine triphosphate binding site of glycogen synthase kinase (GSK)-3β through simulation studies. Out of all 1,2-diphenyline ketone analogues,1, 3, 5, 6-Tetrahydroxyxanthone (Rank = 1), Secalonic acid F (Rank = 2), and Trihydroxy-2-(2,3-dihydroxy-3-methylbutyl)-7-methoxy-8-(3-methyl-2-butenyl) xanthone (Rank = 3) were found to exhibit lowest docking score of -12.07, -11.49, and -11.24 kcal/mol with dissociation constant of 1.37, 3.84, and 5.99 nM, respectively. The molecular dynamic simulation of rank 1 and rank 3 ligands indicated stable interaction throughout the simulation and interaction analyses has shown that the presence of hydroxyl groups at C1, C3, C5, and C6 around 1,2 diphenyline ketone nucleus to influence their binding affinity at the ATP-binding site of GSK-3β. We predicted that 1,3,5,6-Tetrahydroxyxanthone and 1, 3, 6-Trihydroxy-2-(2,3-dihydroxy-3-methylbutyl)-7-methoxy-8-(3-methyl-2-butenyl) xanthone may act as a potential ligand or lead compound to inhibit GSK-3β and also may play an important role in alleviating neurodegenerative diseases.Communicated by Ramaswamy H. Sarma.

Nanovectorization of Ivermectin to avoid overdose of drugs

Ivermectin is an antiparasitic drug that results in the death of the targeted parasites using several mechanical actions. While very well supported, it can induce in rare cases, adverse effects including coma and respiratory failure in case of overdose. This problem should be solved especially in an emergency situation. For instance, the first pandemic of the 21th century was officially declared in early 2020, and while several vaccines around the worlds have been used, an effective treatment against this new strain of coronavirus, better known as SARS-CoV-2, should also be considered, especially given the massive appearance of variants. From all the tested therapies, Ivermectin showed a potential reduction of the viral portability, but sparked significant debate around the dose needed to achieve these positive results. To answer this general question, we propose, using simulations, to show that the nanovectorization of Ivermectin on BN oxide nanosheets can increase the transfer of the drug to its target and thus decrease the quantity of drug necessary to cope with the disease. This first application could help science to develop such nanocargo to avoid adverse effects.Communicated by Ramaswamy H. Sarma.

The Excited State and Charge Transfer of Two Nonfullerene Acceptors from First-Principles Many-Body Green’s Function Theory

Nonfullerene acceptors (NFAs) have shown an outstanding performance upon producing highly efficient and sustainable organic solar cells (OSC). Recently, a growing group of researchers denoted to modify the structures of acceptor−donor−acceptor-type NFAs to raise the power conversion efficiencies (PCEs) when they are blended with a variety of polymer donors in OSC. In 2020, the ketone on the ending groups of BTP-IC were substituted for sulfonyl; the new NFA named BTP-IS was synthetized. The PCE of BTP-IS based OSC is 5.25% higher than that of the BTP-IC device. Based on this, the many-body Green’s function theory, combined with other quantum chemical methods, is conducted to study their ground electronic structures, excited states, and absorption spectra. The ground-state geometries, ionization energies, and the excited state energies are deeply sensitive to exchange-correlation functionals used in calculations. The lowest excited state energies calculated by full-BSE method using DFT-PBE as the starting point is 0.07~0.14 eV smaller than that by TDDFT-PBE method, which is more consistent with experimental data. This provided a methodology for future research on similar NFA systems. The first charge-transfer states and transfer mechanism of two molecules are proposed in this paper. Furthermore, we found that the reason for more efficient charge transport in BTP-IS-based OSC is the larger ionization energies and much weaker electron-hole interaction in BTP-IS. This finding is conducive to the better application of BTP-IS in OSC field.

Computational Screening of Newly Designed Compounds against Coxsackievirus A16 and Enterovirus A71

Outbreaks of hand, foot, and mouth disease (HFMD) that occur worldwide are mainly caused by the Coxsackievirus-A16 (CV-A16) and Enterovirus-A71 (EV-A71). Unfortunately, neither an anti-HFMD drug nor a vaccine is currently available. Rupintrivir in phase II clinical trial candidate for rhinovirus showed highly potent antiviral activities against enteroviruses as an inhibitor for 3C protease (3Cpro). In the present study, we focused on designing 50 novel rupintrivir analogs against CV-A16 and EV-A71 3Cpro using computational tools. From their predicted binding affinities, the five compounds with functional group modifications at P1′, P2, P3, and P4 sites, namely P1′-1, P2-m3, P3-4, P4-5, and P4-19, could bind with both CV-A16 and EV-A71 3Cpro better than rupintrivir. Subsequently, these five analogs were studied by 500 ns molecular dynamics simulations. Among them, P2-m3, the derivative with meta-aminomethyl-benzyl group at the P2 site, showed the greatest potential to interact with the 3Cpro target by delivering the highest number of intermolecular hydrogen bonds and contact atoms. It formed the hydrogen bonds with L127 and K130 residues at the P2 site stronger than rupintrivir, supported by significantly lower MM/PB(GB)SA binding free energies. Elucidation of designed rupintrivir analogs in our study provides the basis for developing compounds that can be candidate compounds for further HFMD treatment.

Structural Characteristics of Glycocins: Unraveling the Role of S-Linked Carbohydrates and Other Structural Elements

Glycocins are antimicrobial peptides with glycosylations, often an S-linked monosaccharide. Their recent structure elucidation has brought forth questions about their mechanisms of action as well as the impact of S-glycosylation on their structural behavior. Here, we investigated structural characteristics of glycocins using a computational approach. Depending on the peptide's class (sublancin- or glycocin F-like), the sugar changes the peptide's flexibility. Also, the presence of glycosylation is necessary for the lack of structure of Asm1. The C-terminal tail in glycocin F-like peptides influenced their structured regions, acting like a regulator. These findings corroborate the versatility of these post-translational modifications, pointing toward their potential use in molecular engineering.

SARS-CoV-2 variant surge and vaccine breakthrough infection: A computational analysis

Coronavirus Delta variant was first detected in India in October of 2020, and it led to a massive second wave of COVID-19 cases in the country. Since then, the highly infectious Delta strain has been spreading globally. The Delta variant and its sub-lineages showed an increased infection rate with a reduced effect of the potential antibody neutralization. The current work is a modeled computational analysis of the mutated receptor-binding domain (RBD) of the SARS-CoV-2 B.1.617 lineage binding with ACE2 and GRP78 to understand the increased strain transmissibility. The cell-surface Glucose Regulated Protein 78 (GRP78) attached to the mutated ACE2-SARS-CoV-2 Spike RBD complex is modeled. The results showed that GRP78 β-substrate-binding domain weakly binds to the wild-type RBD combined with angiotensin-converting enzyme 2 (ACE2) within the SARS-CoV-2 Spike RBD-ACE2 complex. Both GRP78 and ACE2 bind approximately in the same region on the wild-type SARS-CoV-2 Spike RBD surface. On the other hand, GRP78 strongly binds to the mutated SARS-CoV-2 Spike RBD in the RBD-ACE2 complex through the α-substrate-binding domain instead of β-substrate-binding domain in a different region from that of ACE2. The current findings suggest that blocking the main ACE2 pathway may not prevent the interactions between GRP78 and the mutated SARS-CoV-2 Spike RBD, which might introduce an additional avenue into the virus invasion for the host cell if the ACE2 pathway is blocked by the neutralized antibodies. Hence, the peptide satpdb10668 has been proposed as a potential inhibitor of SARS-CoV-2 attachment and virus invasion into the host cell.

Computational Tools to Rationalize and Predict the Self-Assembly Behavior of Supramolecular Gels

Supramolecular gels form a class of soft materials that has been heavily explored by the chemical community in the past 20 years. While a multitude of experimental techniques has demonstrated its usefulness when characterizing these materials, the potential value of computational techniques has received much less attention. This review aims to provide a complete overview of studies that employ computational tools to obtain a better fundamental understanding of the self-assembly behavior of supramolecular gels or to accelerate their development by means of prediction. As such, we hope to stimulate researchers to consider using computational tools when investigating these intriguing materials. In the concluding remarks, we address future challenges faced by the field and formulate our vision on how computational methods could help overcoming them.

1,3,4-oxadiazole conjugates of capsaicin as potent NorA efflux pump inhibitors of Staphylococcus aureus

NorA efflux pump pertaining to the major facilitator superfamily (MFS) is known to play a key role in antibiotic and biocide resistance in Staphylococcus aureus (S. aureus). It accounts for the extrusion of antibiotics like fluoroquinolones (e.g. ciprofloxacin). Several compounds including synthetic and natural products have been identified as potential NorA efflux pump inhibitors (EPIs) and found to restore the antibacterial activity of antibiotics. However, none of the reported EPIs have reached to clinical approval probably due to their high toxicity profiles. Considering the NorA efflux pump inhibitory potential of capsaicin, a series of capsaicin-based 1,3,4 oxadiazole conjugates were prepared and evaluated for ciprofloxacin activity potentiating effect. Among the new capsaicinoids tested, 17i displayed a minimum effective concentration (MEC) of 12.5 µg/mL against NorA overexpressing S. aureus strain (SA1199B), whereas capsaicin showed MEC of 50 µg/mL. The kill kinetics curve for the combination showed that ciprofloxacin at a sub-inhibitory concentration (0.25 × MIC) was equipotent in effect, to its MIC. 17i has significantly decreased the ethidium bromide efflux confirming NorA inhibition as the mode of action. Mutation prevention concentration of the ciprofloxacin was reduced in combination with 17i.In silico studies revealed the binding efficiency and binding affinity of 17i with NorA. This compound may serve as a template for the further drug discovery.

Engineering a multi epitope vaccine against SARS-CoV-2 by exploiting its non structural and structural proteins

SARS-CoV-2, the causative agent behind the ongoing pandemic exhibits an enhanced potential for infection when compared to its related family members- the SARS-CoV and MERS-CoV; which have caused similar disease outbreaks in the past. The severity of the global health burden, increasing mortality rate and the emergent economic crisis urgently demands the development of next generation vaccines. Amongst such emergent next generation vaccines are the multi-epitope subunit vaccines, which hold promise in combating deadly pathogens. In this study we have exploited immunoinformatics applications to delineate a vaccine candidate possessing multiple B and T cells epitopes by utilizing the SARS-CoV-2 non structural and structural proteins. The antigenicity potential, safety, structural stability and the production feasibility of the designed construct was evaluated computationally. Furthermore, due to the known role of human TLR-3 immune receptor in viral sensing, which facilitates host cells activation for an immune response, the vaccine construct was examined for its binding efficiency using molecular docking and molecular dynamics simulation studies, which resulted in strong and stable interactions. Finally, the immune simulation studies suggested an effective immune response on vaccine administration. Overall, the immunoinformatics analysis advocates that the proposed vaccine candidate is safe and immunogenic and therefore can be pushed as a lead for in vitro and in vivo investigations.Communicated by Ramaswamy H. Sarma.

Cytotoxic T-lymphocyte elicited vaccine against SARS-CoV-2 employing immunoinformatics framework

Development of effective counteragents against the novel coronavirus disease (COVID-19) caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) strains, requires clear insights and information for understanding the immune responses associated with it. This global pandemic has pushed the healthcare system and restricted the movement of people and succumbing of the available therapeutics utterly warrants the development of a potential vaccine to contest the deadly situation. In the present study, highly efficacious, immunodominant cytotoxic T-lymphocyte (CTL) epitopes were predicted by advanced immunoinformatics assays using the spike glycoprotein of SARS-CoV2, generating a robust and specific immune response with convincing immunological parameters (Antigenicity, TAP affinity, MHC binder) engendering an efficient viral vaccine. The molecular docking studies show strong binding of the CTL construct with MHC-1 and host membrane specific TLR2 receptors. The molecular dynamics simulation in an explicit system confirmed the stable and robust binding of CTL epitope with TLR2. Steep magnitude RMSD variation and compelling residual fluctuations existed in terminal residues and various loops of the β linker segments of TLR2-epitope (residues 105-156 and 239-254) to about 0.4 nm. The reduced R_g value (3.3 nm) and stagnant SASA analysis (275 nm/S²/N after 8 ns and 5 ns) for protein surface and its orientation in the exposed and buried regions suggests more compactness due to the strong binding interaction of the epitope. The CTL vaccine candidate establishes a high capability to elicit the critical immune regulators, like T-cells and memory cells as proven by the in silico immunization assays and can be further corroborated through in vitro and in vivo assays.

Comprehensive in silico analysis and molecular dynamics of the superoxide dismutase 1 (SOD1) variants related to amyotrophic lateral sclerosis

Amyotrophic Lateral Sclerosis (ALS) is the most frequent motor neuron disorder, with a significant social and economic burden. ALS remains incurable, and the only drugs approved for its treatments confers a survival benefit of a few months for the patients. Missense mutations in superoxide dismutase 1 (SOD1), a major cytoplasmic antioxidant enzyme, has been associated with ALS development, accounting for 23% of its familial cases and 7% of all sporadic cases. This work aims to characterize in silico the structural and functional effects of SOD1 protein variants. Missense mutations in SOD1 were compiled from the literature and databases. Twelve algorithms were used to predict the functional and stability effects of these mutations. ConSurf was used to estimate the evolutionary conservation of SOD1 amino-acids. GROMACS was used to perform molecular dynamics (MD) simulations of SOD1 wild-type and variants A4V, D90A, H46R, and I113T, which account for approximately half of all ALS-SOD1 cases in the United States, Europe, Japan, and United Kingdom, respectively. 233 missense mutations in SOD1 protein were compiled from the databases and literature consulted. The predictive analyses pointed to an elevated rate of deleterious and destabilizing predictions for the analyzed variants, indicating their harmful effects. The ConSurf analysis suggested that mutations in SOD1 mainly affect conserved and possibly functionally essential amino acids. The MD analyses pointed to flexibility and essential dynamics alterations at the electrostatic and metal-binding loops of variants A4V, D90A, H46R, and I113T that could lead to aberrant interactions triggering toxic protein aggregation. These alterations may have harmful implications for SOD1 and explain their association with ALS. Understanding the effects of SOD1 mutations on protein structure and function facilitates the design of further experiments and provides relevant information on the molecular mechanism of pathology, which may contribute to improvements in existing treatments for ALS.

Dual inhibition of SARS-CoV-2 spike and main protease through a repurposed drug, rutin

The global health emergency caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has led to alarming numbers of fatalities across the world. So far the researchers worldwide have not been able to discover a breakthrough in the form of a potent drug or an effective vaccine. Therefore, it is imperative to discover drugs to curb the ongoing menace. In silico approaches using FDA approved drugs can expedite the drug discovery process by providing leads that can be pursued. In this report, two drug targets, namely the spike protein and main protease, belonging to structural and non-structural class of proteins respectively, were utilized to carry out drug repurposing based screening. The exposed nature of the spike protein on the viral surface along with its instrumental role in host infection and the involvement of main protease in processing of polyproteins along with no human homologue make these proteins attractive drug targets. Interestingly, the screening identified a common high efficiency binding molecule named rutin. Further, molecular dynamics simulations in explicit solvent affirmed the stable and sturdy binding of rutin with these proteins. The decreased R_g value (4 nm for spike-rutin and 2.23 nm for main protease-rutin) and stagnant SASA analysis (485 nm/S²/N in spike-rutin and 152 nm/S2/N in main protease-rutin) for protein surface and its orientation in the exposed and buried regions suggests a strong binding interaction of the drug. Further, cluster analysis and secondary structure analysis of complex trajectories validated the conformational changes due to binding of rutin.

Optimization of Molecular Dynamics Simulations of c-MYC1-88-An Intrinsically Disordered System

Many of the proteins involved in key cellular regulatory events contain extensive intrinsically disordered regions that are not readily amenable to conventional structure/function dissection. The oncoprotein c-MYC plays a key role in controlling cell proliferation and apoptosis and more than 70% of the primary sequence is disordered. Computational approaches that shed light on the range of secondary and tertiary structural conformations therefore provide the only realistic chance to study such proteins. Here, we describe the results of several tests of force fields and water models employed in molecular dynamics simulations for the N-terminal 88 amino acids of c-MYC. Comparisons of the simulation data with experimental secondary structure assignments obtained by NMR establish a particular implicit solvation approach as highly congruent. The results provide insights into the structural dynamics of c-MYC^1-88, which will be useful for guiding future experimental approaches. The protocols for trajectory analysis described here will be applicable for the analysis of a variety of computational simulations of intrinsically disordered proteins.

Molecular Determinants Elucidate the Selectivity in Abscisic Acid Receptor and HAB1 Protein Interactions

The abscisic acid (ABA), as a pivotal plant hormone, plays a key role in controlling the life cycle and adapting to the environmental stresses. The receptors of ABA are the Pyrabactin resistance/Pyrabactin resistance-like/regulatory component of ABA receptors (PYR/PYL/RCAR, PYLs for simplicity), which regulate the protein phosphatase 2Cs (PP2Cs) in the signal pathway. As an important ABA-mimicking ligand, Pyrabactin shows the activation function to parts of members of PYLs, such as PYR1 and PYL1. Due to the antagonism of Pyrabactin to PYL2, it was used as a probe to discover a part of ABA receptors. Since then, many researchers have been trying to find out the determinants of the selective regulation of PYLs and PP2Cs interaction. However, the roles of residues on the selective regulation of PYR1/PYL2 and PP2Cs interaction induced by Pyrabactin are still ambiguous. This research investigated the selective activation mechanism of Pyrabactin through the sequence alignment, molecular docking, molecular dynamics simulation, and binding free energy calculation. Furthermore, the electrostatic and hydrophobic interaction differences induced by Pyrabactin and agonists were compared. The results indicate that Leu137/Val114, Ser85/Ser89, and Gly86/Gly90 from the pocket and gate of PYR1/PYL2 are the vital residues for the selective activation of Pyrabactin. Meanwhile, the electrostatic interaction between PP2Cs and PYLs complexed with agonists was improved. This mechanism provides strong support for the design of selective agonists and antagonists.

Effects of the Hydrophobicity of Key Residues on the Characteristics and Stability of Glucose Oxidase on a Graphene Surface

Glucose oxidase (GOx) is one of the most widely investigated enzymes in the field of bioelectrochemistry. It is mainly used for the detection of glucose in solutions and enzyme-based biofuel cells. On the basis of the combination of GOx with graphene, novel nanodevices exceeding conventional limits can be developed. To develop a hybrid enzyme-graphene nanodevice with a good performance, it is important that GOx is deposited well on the graphene surface while maintaining its structure and not impeding the oxidation activity of the GOx. In this study, we propose a method to improve the stability of GOx and secure its immobility on the graphene sheet and its glucose-binding affinity by single-point mutation of GOx using molecular dynamics simulations. We confirm that the structural stability, immobility, and substrate binding affinity of GOx can be modified by changing the hydrophobicity of a key residue. We demonstrate that biosensors or biofuel cells can be redesigned and their properties can be improved by using molecular dynamics simulation.

In silico analysis of the tryptophan hydroxylase 2 (TPH2) protein variants related to psychiatric disorders

The tryptophan hydroxylase 2 (TPH2) enzyme catalyzes the first step of serotonin biosynthesis. Serotonin is known for its role in several homeostatic systems related to sleep, mood, and food intake. As the reaction catalyzed by TPH2 is the rate-limiting step of serotonin biosynthesis, mutations in TPH2 have been associated with several psychiatric disorders (PD). This work undertakes an in silico analysis of the effects of genetic mutations in the human TPH2 protein. Ten algorithms were used to predict the functional and stability effects of the TPH2 mutations. ConSurf was used to estimate the evolutionary conservation of TPH2 amino acids. GROMACS was used to perform molecular dynamics (MD) simulations of TPH2 WT and P260S, R303W, and R441H, which had already been associated with the development of PD. Forty-six TPH2 variants were compiled from the literature. Among the analyzed variants, those occurring at the catalytic domain were shown to be more damaging to protein structure and function. The ConSurf analysis indicated that the mutations affecting the catalytic domain were also more conserved throughout evolution. The variants S364K and S383F were predicted to be deleterious by all the functional algorithms used and occurred at conserved positions, suggesting that they might be deleterious. The MD analyses indicate that the mutations P206S, R303W, and R441H affect TPH2 flexibility and essential mobility at the catalytic and oligomerization domains. The variants P206S, R303W, and R441H also exhibited alterations in dimer binding affinity and stability throughout the simulations. Thus, these mutations may impair TPH2 functional interactions and, consequently, its function, leading to the development of PD. Furthermore, we developed a database, SNPMOL (http://www.snpmol.org/), containing the results presented in this paper. Understanding the effects of TPH2 mutations on protein structure and function may lead to improvements in existing treatments for PD and facilitate the design of further experiments.

Tweaking α -Galactoceramides: Probing the Dynamical Mechanisms of Improved Recognition for Invariant Natural Killer T-cell Receptor in Cancer Immunotherapeutics

BACKGROUND

The last few decades have witnessed groundbreaking research geared towards immune surveillance mechanisms and have yielded significant improvements in the field of cancer immunotherapy. This approach narrows down on the development of therapeutic agents that either activate or enhance the recognitive function of the immune system to facilitate the destruction of malignant cells. The α -galactosylceramide derivative, KRN7000, is an immunotherapeutic agent that has gained attention due to its pharmacological ability to activate CD1d-restricted invariant natural killer T(iNKT) cells with notable potency against cancer cells in mouse models; a therapeutic success was not well replicated in human models. Dual structural modification of KRN7000 entailing the incorporation of hydrocinnamoyl ester on C6" and C4-OH truncation of the sphingoid base led to the development of AH10-7 which, interestingly, exhibited high potency in human cells.

OBJECTIVE/METHODS

Therefore, to gain molecular insights into the structural dynamics and selective mechanisms of AH10-7 for human variants, we employed integrative molecular dynamics simulations and thermodynamic calculations to investigate the inhibitory activities of KRN7000 andAH10-7 on hTCR-CD1d towards activating iNKT.

RESULTS

Interestingly, our findings revealed that AH10-7 exhibited higher affinity binding and structural effects on hTCR-CD1d, as mediated by the incorporated hydrocinnamoyl ester moiety which accounted for stronger intermolecular interactions with 'non-common' binding site residues.

CONCLUSION

Findings extracted from this study further reveal important molecular and structural perspectives that could aid in the design of novel α-GalCer derivatives for cancer immunotherapeutics.

Large-Scale Conformational Changes and Protein Function: Breaking the in silico Barrier

Large-scale conformational changes are essential to link protein structures with their function at the cell and organism scale, but have been elusive both experimentally and computationally. Over the past few years developments in cryo-electron microscopy and crystallography techniques have started to reveal multiple snapshots of increasingly large and flexible systems, deemed impossible only short time ago. As structural information accumulates, theoretical methods become central to understand how different conformers interconvert to mediate biological function. Here we briefly survey current in silico methods to tackle large conformational changes, reviewing recent examples of cross-validation of experiments and computational predictions, which show how the integration of different scale simulations with biological information is already starting to break the barriers between the in silico, in vitro, and in vivo worlds, shedding new light onto complex biological problems inaccessible so far.

Analysis of mutations leading to para-aminosalicylic acid resistance in Mycobacterium tuberculosis

Thymidylate synthase A (ThyA) is the key enzyme involved in the folate pathway in Mycobacterium tuberculosis. Mutation of key residues of ThyA enzyme which are involved in interaction with substrate 2′-deoxyuridine-5′-monophosphate (dUMP), cofactor 5,10-methylenetetrahydrofolate (MTHF), and catalytic site have caused para-aminosalicylic acid (PAS) resistance in TB patients. Focusing on R127L, L143P, C146R, L172P, A182P, and V261G mutations, including wild-type, we performed long molecular dynamics (MD) simulations in explicit solvent to investigate the molecular principles underlying PAS resistance due to missense mutations. We found that these mutations lead to (i) extensive changes in the dUMP and MTHF binding sites, (ii) weak interaction of ThyA enzyme with dUMP and MTHF by inducing conformational changes in the structure, (iii) loss of the hydrogen bond and other atomic interactions and (iv) enhanced movement of protein atoms indicated by principal component analysis (PCA). In this study, MD simulations framework has provided considerable insight into mutation induced conformational changes in the ThyA enzyme of Mycobacterium.

Prediction of MAYV peptide antigens for immunodiagnostic tests by immunoinformatics and molecular dynamics simulations

The Mayaro virus is endemic to South America, and the possible involvement of Aedes spp. mosquitoes in its transmission is a risk factor for outbreaks of greater proportions. The virus causes a potentially disabling illness known as Mayaro fever, which is similar to that caused by the chikungunya virus. The cocirculation of both viruses, with their clinical and structural similarities, and the absence of prophylactic and therapeutic measures highlight the need for studies that seek to understand the Mayaro virus. Using approaches in silico, we identified an antigenic and specific epitope (p_MAYV4) in domain A of the E2 glycoprotein of the Mayaro virus. This epitope was theoretically predicted to be stable and exposed on the surface of the protein, where it showed key properties that enable its interaction with neutralizing antibodies. These characteristics make it an interesting target for the development of immunodiagnostic platforms. Molecular dynamics simulation-based structural analysis showed that the PHE95 residue in the E1 fusion loop region is conserved among Alphavirus family members. PHE95 interacts with the hydrophobic residues of the E2 glycoprotein to form a cage-shaped structure that is critical to assemble and stabilize the E1/E2 heterodimer. These results provide important insights useful for the advancement of diagnostic platforms and the study of therapeutic alternatives.

In silico analysis of PFN1 related to amyotrophic lateral sclerosis

Profilin 1 (PFN1) protein plays key roles in neuronal growth and differentiation, membrane trafficking, and regulation of the actin cytoskeleton. Four natural variants of PFN1 were described as related to ALS, the most common adult-onset motor neuron disorder. However, the pathological mechanism of PFN1 in ALS is not yet completely understood. The goal of this work is to thoroughly analyze the effects of the ALS-related mutations on PFN1 structure and function using computational simulations. Here, PhD-SNP, PMUT, PolyPhen-2, SIFT, SNAP, SNPS&GO, SAAP, nsSNPAnalyzer, SNPeffect4.0 and I-Mutant2.0 were used to predict the functional and stability effects of PFN1 mutations. ConSurf was used for the evolutionary conservation analysis, and GROMACS was used to perform the MD simulations. The mutations C71G, M114T, and G118V, but not E117G, were predicted as deleterious by most of the functional prediction algorithms that were used. The stability prediction indicated that the ALS-related mutations could destabilize PFN1. The ConSurf analysis indicated that the mutation C71G, M114T, E117G, and G118V occur in highly conserved positions. The MD results indicated that the studied mutations could affect the PFN1 flexibility at the actin and PLP-binding domains, and consequently, their intermolecular interactions. It may be therefore related to the functional impairment of PFN1 upon C71G, M114T, E117G and G118V mutations, and their involvement in ALS development. We also developed a database, SNPMOL (http://www.snpmol.org/), containing the results presented on this paper for biologists and clinicians to exploit PFN1 and its natural variants.

In silico analysis of the V66M variant of human BDNF in psychiatric disorders: An approach to precision medicine

Brain-derived neurotrophic factor (BDNF) plays an important role in neurogenesis and synapse formation. The V66M is the most prevalent BDNF mutation in humans and impairs the function and distribution of BDNF. This mutation is related to several psychiatric disorders. The pro-region of BDNF, particularly position 66 and its adjacent residues, are determinant for the intracellular sorting and activity-dependent secretion of BDNF. However, it has not yet been fully elucidated. The present study aims to analyze the effects of the V66M mutation on BDNF structure and function. Here, we applied nine algorithms, including SIFT and PolyPhen-2, for functional and stability prediction of the V66M mutation. The complete theoretical model of BNDF was generated by Rosetta and validated by PROCHECK, RAMPAGE, ProSa, QMEAN and Verify-3D algorithms. Structural alignment was performed using TM-align. Phylogenetic analysis was performed using the ConSurf server. Molecular dynamics (MD) simulations were performed and analyzed using the GROMACS 2018.2 package. The V66M mutation was predicted as deleterious by PolyPhen-2 and SIFT in addition to being predicted as destabilizing by I-Mutant. According to SNPeffect, the V66M mutation does not affect protein aggregation, amyloid propensity, and chaperone binding. The complete theoretical structure of BDNF proved to be a reliable model. Phylogenetic analysis indicated that the V66M mutation of BDNF occurs at a non-conserved position of the protein. MD analyses indicated that the V66M mutation does not affect the BDNF flexibility and surface-to-volume ratio, but affects the BDNF essential motions, hydrogen-bonding and secondary structure particularly at its pre and pro-domain, which are crucial for its activity and distribution. Thus, considering that these parameters are determinant for protein interactions and, consequently, protein function; the alterations observed throughout the MD analyses may be related to the functional impairment of BDNF upon V66M mutation, as well as its involvement in psychiatric disorders.

The Effect of Cofactor Binding on the Conformational Plasticity of the Biological Receptors in Artificial Metalloenzymes: The Case Study of LmrR

The design of Artificial Metalloenzymes (ArMs), which result from the incorporation of organometallic cofactors into biological structures, has grown steadily in the last two decades and important new-to-Nature reactions have been reached. These type of exercises could greatly benefit from an understanding of the structural impact that the inclusion of organometallic moieties may have on the biological host. To date though, our understanding of this phenomenon is highly partial. This lack of knowledge is one of the elements that condition that first-generation ArMs generally display relatively poor catalytic profiles. In this work, we approach this matter by assessing the dynamics and stability of a series of ArMs resulting from the inclusion, via different anchoring strategies, of a variety of organometallic cofactors into the Lactococcal multidrug resistance regulator (LmrR) protein. To this aim, we coupled standard force field-based techniques such as Protein-Ligand Docking and Molecular Dynamics simulations with a variety of trajectory convergence analyses, capable of assessing both the stability and flexibility of the different systems under study upon the binding of cofactors. Together with the experimental evidence obtained in other studies, we provide an overview on how these changes can affect the catalytic outcomes obtained from the different ArMs. Fundamentally, our results show that the convergence analysis used in this work can assess how the inclusion of synthetic metallic cofactors in proteins can condition different structural modulations of their host. Those conformational modifications are key to the success of the desired catalytic activity and their proper identification can be wisely used to improve the quality and the rate of success of the ArMs.

High-throughput computational pipeline for 3-D structure preparation and in silico protein surface property screening: A case study on HBcAg dimer structures

Knowledge-based experimental design can aid biopharmaceutical high-throughput screening (HTS) experiments needed to identify critical manufacturability parameters. Prior knowledge can be obtained via computational methods such as protein property extraction from 3-D protein structures. This study presents a high-throughput 3-D structure preparation and refinement pipeline that supports structure screenings with an automated and data-dependent workflow. As a case study, three chimeric virus-like particle (VLP) building blocks, hepatitis B core antigen (HBcAg) dimers, were constructed. Molecular dynamics (MD) refinement quality, speed, stability, and correlation to zeta potential data was evaluated using different MD simulation settings. Settings included 2 force fields (YASARA2 and AMBER03) and 2 pKa computation methods (YASARA and H++). MD simulations contained a data-dependent termination via identification of a 2 ns Window of Stability, which was also used for robust descriptor extraction. MD simulation with YASARA2, independent of pKa computation method, was found to be most stable and computationally efficient. These settings resulted in a fast refinement (6.6-37.5 h), a good structure quality (-1.17--1.13) and a strong linear dependence between dimer surface charge and complete chimeric HBcAg VLP zeta potential. These results indicate the computational pipeline's applicability for early-stage candidate assessment and design optimization of HTS manufacturability or formulability experiments.

How peptide/MHC presence affects the dynamics of the LC13 T-cell receptor

The interaction between T-cell receptors (TCRs) of T-cells and potentially immunogenic peptides presented by MHCs of antigen presenting cells is one of the most important mechanisms of the adaptive human immune system. A large number of structural simulations of the TCR/peptide/MHC system have been carried out. However, to date no study has investigated the differences of the dynamics between free TCRs and pMHC bound TCRs on a large scale. Here we present a study totalling 37 100 ns investigating the LC13 TCR in its free form as well as in complex with HLA-B*08:01 and different peptides. Our results show that the dynamics of the bound and unbound LC13 TCR differ significantly. This is reflected in (a) expected results such as an increased flexibility and increased solvent accessible surface of the CDRs of unbound TCR simulations but also in (b) less expected results such as lower CDR distances and compactness as well as alteration in the hydrogen bond network around CDR3α of unbound TCR simulations. Our study further emphasises the structural flexibility of TCRs and confirms the importance of the CDR3 loops for the adoption to MHC.

Dynamics and binding interactions of peptide inhibitors of dengue virus entry

In this study, we investigate the binding interactions of two synthetic antiviral peptides (DET2 and DET4) on type II dengue virus (DENV2) envelope protein domain III. These two antiviral peptides are designed based on the domain III of the DENV2 envelope protein, which has shown significant inhibition activity in previous studies and can be potentially modified further to be active against all dengue strains. Molecular docking was performed using AutoDock Vina and the best-ranked peptide-domain III complex was further explored using molecular dynamics simulations. Molecular mechanics-Poisson-Boltzmann surface area (MM-PBSA) was used to calculate the relative binding free energies and to locate the key residues of peptide-protein interactions. The predicted binding affinity correlated well with the previous experimental studies. DET4 outperformed DET2 and is oriented within the binding site through favorable vdW and electrostatic interactions. Pairwise residue decomposition analysis has revealed several key residues that contribute to the binding of these peptides. Residues in DET2 interact relatively lesser with the domain III compared to DET4. Dynamic cross-correlation analysis showed that both the DET2 and DET4 trigger different dynamic patterns on the domain III. Correlated motions were seen between the residue pairs of DET4 and the binding site while binding of DET2 results in anti-correlated motion on the binding site. This work showcases the use of computational study in elucidating and explaining the experiment observation on an atomic level.

A combination of bioactive and nonbioactive alkyl-peptides form a more stable nanofiber structure for differentiating neural stem cells: a molecular dynamics simulation survey

Self-assembling alkyl-peptides are important molecules due to their ability to construct nano-level structures such as nanofibers to be utilized as tissue engineering scaffolds. The bioactive epitope of FAQRVPP which acts as neural stem cells (NSCs) outgrowth inducing factor is used in nanofiber structures. Based on previous experimental studies the density and distribution pattern of the epitopes on the surface of the nanofibers plays an important role in the differentiation function efficiency. We decided to survey and compare the stability of two pre-constructed fiber structures in the forms of all-functionalized nanofiber (containing only bioactive alkyl-peptides) and distributed functionalized nanofiber (a combination of nonbioactive and bioactive alkyl-peptides with ratio 2:1). Our findings reveal that the all-functionalized fiber shows an unstable structure and is split into intermediate micelle-like structures to reduce compactness and steric hindrance of functional epitopes whereas the distributed functionalized fiber shows an integrated stable nanofiber with a more amount of beta sheets that are well-organized and oriented around the hydrophobic core. The hydrogen bonds and energy profiles of the structures indicate the role of hydrophobic interactions during the alkyl-chain core formation and the important role of electrostatic interactions and hydrogen bond network in the stability of the final structures. Finally, it seems that the possibility of the presence of intermediate structure is increased in the all-functionalized nanofiber environment, and it can reduce functional efficiency of the scaffolds. These findings can help to design more efficient nanofiber structures with different goals in scaffolds for tissue engineering. Abbreviations MD Molecular Dynamics NSCs Neural Stem Cells PME Particle mesh Ewald RDF Radial Distribution Function RG Radius of gyration RASA Relative Accessible Surface Area RMSD Root Mean Square Deviations SASA Solvent Accessible Surface Area. Communicated by Ramaswamy H. Sarma.

High throughput nonparametric probability density estimation

In high throughput applications, such as those found in bioinformatics and finance, it is important to determine accurate probability distribution functions despite only minimal information about data characteristics, and without using human subjectivity. Such an automated process for univariate data is implemented to achieve this goal by merging the maximum entropy method with single order statistics and maximum likelihood. The only required properties of the random variables are that they are continuous and that they are, or can be approximated as, independent and identically distributed. A quasi-log-likelihood function based on single order statistics for sampled uniform random data is used to empirically construct a sample size invariant universal scoring function. Then a probability density estimate is determined by iteratively improving trial cumulative distribution functions, where better estimates are quantified by the scoring function that identifies atypical fluctuations. This criterion resists under and over fitting data as an alternative to employing the Bayesian or Akaike information criterion. Multiple estimates for the probability density reflect uncertainties due to statistical fluctuations in random samples. Scaled quantile residual plots are also introduced as an effective diagnostic to visualize the quality of the estimated probability densities. Benchmark tests show that estimates for the probability density function (PDF) converge to the true PDF as sample size increases on particularly difficult test probability densities that include cases with discontinuities, multi-resolution scales, heavy tails, and singularities. These results indicate the method has general applicability for high throughput statistical inference.

Human DHEA sulfation requires direct interaction between PAPS synthase 2 and DHEA sulfotransferase SULT2A1

The high-energy sulfate donor 3′-phosphoadenosine-5′-phosphosulfate (PAPS), generated by human PAPS synthase isoforms PAPSS1 and PAPSS2, is required for all human sulfation pathways. Sulfotransferase SULT2A1 uses PAPS for sulfation of the androgen precursor dehydroepiandrosterone (DHEA), thereby reducing downstream activation of DHEA to active androgens. Human PAPSS2 mutations manifest with undetectable DHEA sulfate, androgen excess, and metabolic disease, suggesting that ubiquitous PAPSS1 cannot compensate for deficient PAPSS2 in supporting DHEA sulfation. In knockdown studies in human adrenocortical NCI-H295R1 cells, we found that PAPSS2, but not PAPSS1, is required for efficient DHEA sulfation. Specific APS kinase activity, the rate-limiting step in PAPS biosynthesis, did not differ between PAPSS1 and PAPSS2. Co-expression of cytoplasmic SULT2A1 with a cytoplasmic PAPSS2 variant supported DHEA sulfation more efficiently than co-expression with nuclear PAPSS2 or nuclear/cytosolic PAPSS1. Proximity ligation assays revealed protein–protein interactions between SULT2A1 and PAPSS2 and, to a lesser extent, PAPSS1. Molecular docking studies showed a putative binding site for SULT2A1 within the PAPSS2 APS kinase domain. Energy-dependent scoring of docking solutions identified the interaction as specific for the PAPSS2 and SULT2A1 isoforms. These findings elucidate the mechanistic basis for the selective requirement for PAPSS2 in human DHEA sulfation.

Interactions of 2'-O-methyl oligoribonucleotides with the RNA models of the 30S subunit A-site

Synthetic oligonucleotides targeting functional regions of the prokaryotic rRNA could be promising antimicrobial agents. Indeed, such oligonucleotides were proven to inhibit bacterial growth. 2’-O-methylated (2’-O-Me) oligoribonucleotides with a sequence complementary to the decoding site in 16S rRNA were reported as inhibitors of bacterial translation. However, the binding mode and structures of the formed complexes, as well as the level of selectivity of the oligonucleotides between the prokaryotic and eukaryotic target, were not determined. We have analyzed three 2’-O-Me oligoribonucleotides designed to hybridize with the models of the prokaryotic rRNA containing two neighboring aminoglycoside binding pockets. One pocket is the paromomycin/kanamycin binding site corresponding to the decoding site in the small ribosomal subunit and the other one is the close-by hygromycin B binding site whose dynamics has not been previously reported. Molecular dynamics (MD) simulations, as well as isothermal titration calorimetry, gel electrophoresis and spectroscopic studies have shown that the eukaryotic rRNA model is less conformationally stable (in terms of hydrogen bonds and stacking interactions) than the corresponding prokaryotic one. In MD simulations of the eukaryotic construct, the nucleotide U1498, which plays an important role in correct positioning of mRNA during translation, is flexible and spontaneously flips out into the solvent. In solution studies, the 2’-O-Me oligoribonucleotides did not interact with the double stranded rRNA models but all formed stable complexes with the single-stranded prokaryotic target. 2’-O-Me oligoribonucleotides with one and two mismatches bound less tightly to the eukaryotic target. This shows that at least three mismatches between the 2’-O-Me oligoribonucleotide and eukaryotic rRNA are required to ensure target selectivity. The results also suggest that, in the ribosome environment, the strand invasion is the preferred binding mode of 2’-O-Me oligoribonucleotides targeting the aminoglycoside binding sites in 16S rRNA.