Dynamical Cross-correlation Map Research Articles

The two-step strategy for enhancing the specific activity and thermostability of alginate lyase AlyG2 with mechanism for improved thermostability

To overcome the trade-off challenge encountered in the engineering of alginate lyase AlyG2 from Seonamhaeicola algicola Gy8T and to expand its potential industrial applications, we devised a two-step strategy encompassing activity enhancement followed by thermal stability engineering. To enhance the specific activity of efficient AlyG2, we strategically substituted residues with bulky steric hindrance proximal to the active pocket with glycine or alanine. This led to the generation of three promising positive mutants, with particular emphasis on the T91S mutant, exhibiting a 1.91-fold specific activity compared to the wild type. To mitigate the poor thermal stability of T91S, mutants with negative ΔΔG values in the thermal flexibility region were screened out. Notably, the S72Ya mutant not only displayed 17.96 % further increase in specific activity but also exhibited improved stability compared to T91S, manifesting as a remarkable 30.97 % increase in relative activity following a 1-hour incubation at 42 °C. Furthermore, enhanced kinetic stability was observed. To gain deeper insights into the mechanism underlying the enhanced thermostability of the S72Ya mutant, we conducted molecular dynamics simulations, principal component analysis (PCA), dynamic cross-correlation map (DCCM), and free energy landscape (FEL) analysis. The results unveiled a reduction in the flexibility of the surface loop, a stronger correlation dynamic and a narrower motion subspace in S72Ya system, along with the formation of more stable hydrogen bonds. Collectively, our findings suggest amino acids substitutions resulting in smaller side chains proximate to the active site can positively impact enzyme activity, while reducing the flexibility of surface loops emerges as a pivotal factor in conferring thermal stability. These insights offer valuable guidance and a framework for the engineering of other enzyme types.

Molecular dynamics simulation analysis of structural dynamic cross correlation induced by odorant hydrogen-bonding in mouse eugenol ol- factory receptor.

Structural fluctuations and dynamic cross-correlations in the mouse eugenol olfactory receptor (Olfr73) were studied by molecular dynamics (MD) simulation to characterize the dynamic response of the protein upon ligand binding. The initial structure was generated by the artificial intelligence tool AlphaFold2 due to the current lack of experimental data. We focused on the hydrogen (H) bond of the odorant eugenol to Ser113, Asn207, and Tyr260 of the receptor protein, the importance of which has been suggested by previous experimental studies. The H-bond was not observed in docking simulations, but in subsequent MD simulations the H-bond to Ser113 was formed in 2-4 ns. The lifetime of the H-bond was in the range of 1-20 ns. On the trajectory with the most stable (20 ns) H-bond, the structural fluctuation of the α-carbon atoms of the receptor main chain was studied by calculating the root mean square fluctuations, the dynamic cross-correlation map, and the time-dependent dynamic cross-correlation. The analysis suggested a correlation transfer pathway Ser113 → Phe182 → (Leu259 or Tyr260) → Tyr291 induced by the ligand binding with a time scale of 4-6 ns.

Accelerated molecular dynamics study of the interaction mechanism between small molecule inhibitors and phosphoglycerate mutase 1.

In 2020, cancer-related deaths reached 9.96 million globally, of which China accounted for 3 million, ranking first in the world. Phosphoglycerate mutase 1 (PGAM1) is a key metabolic enzyme in glycolysis, catalysing the conversion of 3-phosphoglycerate to 2-phosphoglycerate. Based on the excellent anticancer activity of PGMI-004A and HKB99, new small molecules with an anthraquinone core were synthesised to inhibit tumour growth. Developing small molecules with an anthraquinone core targeting PGAM1 may be an effective strategy for treating cancer. In this study, accelerated molecular dynamics (aMD) simulation, dynamic cross-correlation map (DCCM) calculation, principal component analysis (PCA) and free energy landscape (FEL) analysis were used to analyse conformational changes of PGAM1 caused by binding of inhibitors 8KX, 9HU and HKB. DCCM calculations and PCA showed that inhibitor binding significantly affected the kinetic behaviour of PGAM1 and conformational rearrangement of PGAM1. The binding ability and mechanism of 8KX, 9HU and HKB to PGAM1 were studied using the molecular mechanics generalised Born surface area (MM-GBSA) method. The results showed that compared with 8KX, the binding ability of 9HU and HKB to PGAM1 was enhanced by sulphonamide reversal and aminocarboxyl trifluoromethyl substitution. There were several hydrophobic interactions between inhibitors and PGAM1, providing significant contributions for inhibitor binding. Calculation of residue-based free energy decomposition revealed that F22, R90, Y92, L95, V112, W115, R116, V121, P123, P124, R191 and M206 were key residues of the PGAM1-inhibitor interaction and could be used as effective targets for designing drugs that inhibit the activity of PGAM1.

Integrated gene expression profiling and functional enrichment analyses to discover biomarkers and pathways associated with Guillain-Barré syndrome and autism spectrum disorder to identify new therapeutic targets

Guillain-Barré syndrome (GBS) is one of the most prominent and acute immune-mediated peripheral neuropathy, while autism spectrum disorders (ASD) are a group of heterogeneous neurodevelopmental disorders. The complete mechanism regarding the neuropathophysiology of these disorders is still ambiguous. Even after recent breakthroughs in molecular biology, the link between GBS and ASD remains a mystery. Therefore, we have implemented well-established bioinformatic techniques to identify potential biomarkers and drug candidates for GBS and ASD. 17 common differentially expressed genes (DEGs) were identified for these two disorders, which later guided the rest of the research. Common genes identified the protein-protein interaction (PPI) network and pathways associated with both disorders. Based on the PPI network, the constructed hub gene and module analysis network determined two common DEGs, namely CXCL9 and CXCL10, which are vital in predicting the top drug candidates. Furthermore, coregulatory networks of TF-gene and TF-miRNA were built to detect the regulatory biomolecules. Among drug candidates, imatinib had the highest docking and MM-GBSA score with the well-known chemokine receptor CXCR3 and remained stable during the 100 ns molecular dynamics simulation validated by the principal component analysis and the dynamic cross-correlation map. This study predicted the gene-based disease network for GBS and ASD and suggested prospective drug candidates. However, more in-depth research is required for clinical validation. Communicated by Ramaswamy H. Sarma

Molecular dynamics simulations reveal phosphorylation-induced conformational dynamics of the fibroblast growth factor receptor 1 kinase

The Fibroblast Growth Factor Receptor1 (FGFR1) kinase wields exquisite control on cell fate, proliferation, differentiation, and homeostasis. An imbalance of FGFR1 signaling leads to several pathogeneses of diseases ranging from multiple cancers to allergic and neurodegenerative disorders. In this study, we investigated the phosphorylation-induced conformational dynamics of FGFR1 in apo and ATP-bound states via all-atom molecular dynamics simulations. All simulations were performed for 2 × 2 µs. We have also investigated the energetics of the binding of ATP to FGFR1 using the molecular mechanics Poisson-Boltzmann scheme. Our study reveals that the FGFR1 kinase can reach a fully active configuration through phosphorylation and ATP binding. A 3–10 helix formation in the activation loop signifies its rearrangement leading to stability upon ATP binding. The interaction of phosphorylated tyrosine (pTyr654) with positively charged residues forms strong salt-bridge interactions, driving the compactness of the structure. The dynamic cross-correlation map reveals phosphorylation enhances correlated motions and reduces anti-correlated motions between different domains. We believe that the mechanistic understanding of large-conformational changes upon the activation of the FGFR1 kinase will aid the development of novel targeted therapeutics. Communicated by Ramaswamy H. Sarma

A Novel Inhibitor of DKK1/LRP6 Interactions Against the Alzheimer Disease: An Insilco Approach

The activation of the Wnt signaling pathway is implicated in a neuroprotective mechanism against the Alzheimer disease. When this pathway is blocked, it activates GSK3 beta, leading to tau hyperphosphorylation and the apoptosis of neurons. Dickkopf-related protein 1 (DKK1) is a protein that competes with the Wnt ligand for the low-density lipoprotein receptor–related protein 6 (LRP6) receptor’s binding, interrupting the Wnt-induced Fzd-Wnt-LRP6 complex. This counteracts Wnt’s neuroprotective effect and contributes to the progression of the Alzheimer disease. The aim of this study was to use in silico approach to develop new agents that can combat the Alzheimer disease by targeting the interaction between DKK1 and LRP6. To achieve this, we conducted a virtual screening (Vsw) of the Asinex-CNS database library (n = 54 513) compounds against a generated grid in LRP6 protein. From this screening, we selected 6 compounds based on their docking score and performed molecular mechanics-generalized Born surface area (MM-GBSA) binding energy calculations on the selected ligands. Next, we evaluated the Absorption, Distribution, Metabolism, and Excretion (ADME) results of the 6 screened compounds using the Quick prop module of Schrödinger. We then employed several computational techniques, including PCA (Principal Component Analysis), DCCM (Dynamic Cross-Correlation Map), molecular dynamics simulation, and molecular mechanics/Poisson-Boltzmann surface area (MM/PBSA)–based negative binding free energy (BFE) calculation, to further analyze the compounds. Our extensive computational analysis resulted in the identification of 3 potential hits, LAS 29757582, LAS 29984441, and LAS 29757942. These compounds were found to block the interaction of DKK1 with LRP6 (A and B interface) protein, and their potential as therapeutic agents was supported by negative BFE calculation. Therefore, these compounds show potential as possible therapeutic agents for treating the Alzheimer disease through targeting the interaction between DKK1 and LRP6.

Flap sub-domain dynamics of serine-threonine phosphatase (Stp1) of Staphylococcus aureus: an accelerated molecular dynamics simulation study

Vancomycin and daptomycin are commonly used glycopeptide antibiotics to cure Gram-positive staphylococcal infections. The clinical isolates of mutant Staphylococcus aureus strains, Methicillin-Resistant (MRSA) and Vancomycin-Resistant (VRSA), have developed resistance against these antibiotics. A recently discovered Serine/threonine phosphatase (Stp1) is an Mn+2 containing protein at the active site with a flap sub-domain that participates in the phospho-signaling system of bacterial cell wall formation. The flap sub-domain probably regulates substrates recruitment and release with an extra Mn+2, possibly highly flexible as in the other homologous family of proteins. In this study, the flap sub-domain has been sampled with conventional and accelerated molecular dynamics (cMD and aMD) simulations to get other sub-optimal conformational states of the protein that are nearly impossible to observe through experimental methods. Trajectory analysis has shown that protein remained static in cMD while dynamic in aMD with RMSD of ∼2Å and ∼3Å, respectively. Accelerated MD has shown greater flexibility of ∼4 Å in the flap sub-domain, while cMD only captured a deviation of ∼ 2 Å. Later, the dynamic cross-correlation map (DCCM) confirmed that the flap sub-domain is significantly more flexible than the other part of the structure, indicating its role in substrate regulation. Secondary structure transition in the flap sub-domain, i.e. 3-10 helix and turn (PRO159 - ILE163) region of the flap sub-domain shifted into α-helix, which is a more stable structure. Further, the trajectory has been clustered, and conformational states extracted, which may be exploited in structure-based antibiotics discovery.

Investigation of the structural dynamics of a knotted protein and its unknotted analog using molecular dynamics.

The role of knots in proteins remains elusive. Some studies suggest an impact on stability; the difficulty in comparing systems to assess this effect, however, has been a significant challenge. In this study, we produced and analyzed molecular dynamic trajectories considering three different temperatures of two variants of ornithine transcarbamylase (OTC), only one of which has a 31 knot, in order to evaluate the relative stability of the two molecules. RMSD showed equilibrated structures for the produced trajectories, and RMSF showed subtle differences in flexibility. In the knot moiety, the knotted protein did not show a great deal of fluctuation at any temperature. For the unknotted protein, the residue GLY243 showed a high fluctuation in the corresponding moiety. The fraction of native contacts (Q) showed a similar profile at all temperatures, with the greatest decrease by 436K. The investigation of conformational behavior with principal component analysis (PCA) and dynamic cross-correlation map (DCCM) showed that knotted protein is less likely to undergo changes in its conformation under the conditions employed compared to unknotted. PCA data showed that the unknotted protein had greater dispersion in its conformations, which suggests that it has a greater capacity for conformation transitions in response to thermal changes. DCCM graphs comparing the 310K and 436K temperatures showed that the knotted protein had less change in its correlation and anti-correlation movements, indicating stability compared to the unknotted.

The molecular docking and molecular dynamics study of flavonol synthase and flavonoid 3’-monooxygenase enzymes involved for the enrichment of kaempferol

Kaempferol is a natural flavonol that shows many pharmacological properties including anti-inflammatory, antioxidant, anticancer, antidiabetic activities etc. It has been reported in many vegetables, fruits, herbs and medicinal plants. The enzyme flavonol synthase (FLS, EC 1.14.20.6) catalyses the conversion of dihydroflavonols to flavonols. Whereas flavonoid 3’-monooxygenase (F3’H, EC 1.14.14.82) catalyses the hydroxylation of dihydroflavonol, and flavonol. FLS is involved in the synthesis of the kaempferol whereas F3’H causes degradation of kaempferol. The present study aimed to analyse the binding affinity, stability and activating activity of enzyme FLS as well as inhibitory activity of enzyme F3’H involved in the enrichment of the kaempferol using the in-silico approaches. Computational study for physico-chemical properties, conserved domain identification, 3-D structure prediction and its validation, conservation analysis, molecular docking followed by molecular dynamics analysis of FLS and F3’H, protein-activator (FLS-LIG Complex) and protein-inhibitor (F3’H-LIG Complex) complexes have been performed. Other structural analyses like root mean square fluctuation (RMSF), root mean square deviation (RMSD), surface area solvent accessibility (SASA), radius of gyration (Rg), hydrogen bond analysis, principal component analysis (PCA), Poisson-Boltzmann analysis (MM_PBSA) and the dynamic cross correlation map (DCCM) analysis to explore the structural, functional and thermodynamic stability of the proteins and the complexes were also studied. The molecular docking result showed that FLS binds strongly with the activator ascorbate (CID _54670067) while F3’H binds with the inhibitor ketoconazole (CID_456201). The most powerful inhibitor (ketoconazole for F3’H) and activator (ascorbate for FLS) is determined by computing the thermodynamic binding free energy through MM_PBSA analysis. The current work provides wide-ranging structural and functional information about FLS and F3’H enzymes showing detailed molecular mechanism of kaempferol biosynthesis and its degradation and hence kaempferol enrichment. Finding of the present work opens up new possibilities for future research towards enrichment of kaempferol by using activator (ascorbate) for FLS and inhibitor (ketoconazole) for F3’H as well as for its large-scale production using in vitro approaches. Communicated by Ramaswamy H. Sarma

Deciphering the binding mechanism of inhibitors of the SARS-CoV-2 main protease through multiple replica accelerated molecular dynamics simulations and free energy landscapes.

The pneumonia outbreak caused by the SARS-CoV-2 virus poses a serious threat to human health and the world economy. The development of safe and highly effective antiviral drugs is of great significance for the treatment of COVID-19. The main protease (Mpro) of SARS-CoV-2 is a key enzyme for viral replication and transcription and has no homolog in humans. Therefore, the Mpro is an ideal target for the design of drugs against COVID-19. Insights into the inhibitor-Mpro binding mechanism and conformational changes of the Mpro are essential for the design of potent drugs that target the Mpro. In this study, we analyzed the conformational changes of the Mpro that are induced by the binding of three inhibitors, YTV, YSP and YU4, using multiple replica accelerated molecular dynamics (MR-aMD) simulations, dynamic cross-correlation map (DCCM) calculations, principal component analysis (PCA), and free energy landscape (FEL) analysis. The results from DCCM calculations and PCA show that the binding of inhibitors significantly affects the kinetic behavior of the Mpro and induces a conformational rearrangement of the Mpro. The binding ability and binding mechanism of YTV, YSP and YU4 to the Mpro were investigated using the molecular mechanics Poisson-Boltzmann surface area (MM-PBSA) method. The results indicate that substitution of the tert-butanol group by methylbenzene and trifluoromethyl groups enhances the binding ability of YSP and YU4 to the Mpro compared with YTV; moreover, massive hydrophobic interactions are detected between the inhibitors and the Mpro. Meanwhile, T25, L27, H41, M49, N142, G143, C145, M165, E166 and Q189 are identified as the key residues for inhibitor-Mpro interactions using residue-based free energy decomposition calculations, which can be employed as efficient targets in the design of drugs that inhibit the activity of the Mpro.

Investigating potency of TMC-126 against wild-type and mutant variants of HIV-1 protease: a molecular dynamics and free energy study

ABSTRACT A detailed computational study was performed to investigate the conformational changes of flap region and the mechanism underlying the binding of the inhibitor TMC-126 to HIV-1 protease (PR1) and its mutant variants through molecular dynamics simulations in conjunction with the molecular mechanics Poisson–Boltzmann (MM-PBSA) free energy calculation. Further, we have studied the effectiveness of the inhibitor against HIV-2 protease (PR2). The MM-PBSA calculation suggests that TMC-126 loses its potency against mutant variants and PR2 compared to wild-type PR1 mainly due to the loss in intermolecular electrostatic interactions. The potency of the inhibitor decreases in the order: wild type PR1 > M46L > MDR20 > I50V > PR2 > V32I > A28S. Our study reveals that the flap of PR1 adopts a semi-open conformation due to the mutation I50V or MDR20. The dissimilar nature of the movement of the flap tip of both monomers is evident from the dynamic cross-correlation map. The protein structural network analysis displays that mutation causes structural rearrangements and changes the communication path between residues. Overall, we believe our study may help explore and accelerate the development of novel HIV-1/HIV-2 protease inhibitors with better potency.

Equally Weighted Multiscale Elastic Network Model and Its Comparison with Traditional and Parameter-Free Models.

Dynamical properties of proteins play an essential role in their function exertion. The elastic network model (ENM) is an effective and efficient tool in characterizing the intrinsic dynamical properties encoded in biomacromolecule structures. The Gaussian network model (GNM) and anisotropic network model (ANM) are the two often-used ENM models. Here, we introduce an equally weighted multiscale ENM (equally weighted mENM) based on the original mENM (denoted as mENM), in which fitting weights of Kirchhoff/Hessian matrixes in mENM are removed since they neglect the details of pairwise interactions. Then, we perform its comparison with the mENM, traditional ENM, and parameter-free ENM (pfENM) in reproducing dynamical properties for the six representative proteins whose molecular dynamics (MD) trajectories are available in http://mmb.pcb.ub.es/MoDEL/. In the results, for B-factor prediction, mENM performs best, while the equally weighted mENM performs also well, better than the traditional ENM and pfENM models. As to the dynamical cross-correlation map calculation, mENM performs worst, while the results produced from the equally weighted mENM and pfENM models are close to those from MD trajectories with the latter a little better than the former. Furthermore, encouragingly, the equally weighted mANM displays the best performance in capturing the functional motional modes, followed by pfANM and traditional ANM models, while the mANM fails in all the cases. This work is helpful for strengthening the understanding of the elastic network model and provides a valuable guide for researchers to utilize the model to explore protein dynamics.

Antitussive noscapine and antiviral drug conjugates as arsenal against COVID-19: a comprehensive chemoinformatics analysis

Coronavirus pandemic has caused a vast number of deaths worldwide. Thus creating an urgent need to develop effective counteragents against novel coronavirus disease (COVID-19). Many antiviral drugs have been repurposed for treatment but implicated minimal recovery, which further advanced the need for clearer insights and innovation to derive effective therapeutics. Strategically, Noscapine, an approved antitussive drug with positive effects on lung linings may show favorable outcomes synergistically with antiviral drugs in trials. Hence, we have theoretically examined the combinatorial drug therapy by culminating the existing experimental results with in silico analyses. We employed the antitussive noscapine in conjugation with antiviral drugs (Chloroquine, Umifenovir, Hydroxychloroquine, Favlplravir and Galidesivir). We found that Noscapine-Hydroxychloroquine (Nos-Hcq) conjugate has strong binding affinity for the main protease (Mpro) of SARS-CoV-2, which performs key biological function in virus infection and progression. Nos-Hcq was analyzed through molecular dynamics simulation. The MD simulation for 100 ns affirmed the stable binding of conjugation unprecedentedly through RMSD and radius of gyration plots along with critical reaction coordinate binding free energy profile. Also, dynamical residue cross-correlation map with principal component analysis depicted the stable binding of Nos-Hcq conjugate to Mpro domains with optimal secondary structure statistics of complex dynamics. Also, we reveal the drugs with stable binding to major domains of Mpro can significantly improve the work profile of reaction coordinates, drug accession and inhibitory regulation of Mpro. The designed combinatorial therapy paves way for further prioritized in vitro and in vivo investigations for drug with robust binding against Mpro of SARS-CoV-2.

Molecular Binding Mechanism and Pharmacology Comparative Analysis of Noscapine for Repurposing against SARS-CoV-2 Protease.

Originating in the city of Wuhan in China in December 2019, COVID-19 has emerged now as a global health emergency with a high number of deaths worldwide. COVID-19 is caused by a novel coronavirus, referred to as severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), resulting in pandemic conditions around the globe. We are in the battleground to fight against the virus by rapidly developing therapeutic strategies in tackling SARS-CoV-2 and saving human lives from COVID-19. Scientists are evaluating several known drugs either for the pathogen or the host; however, many of them are reported to be associated with side effects. In the present study, we report the molecular binding mechanisms of the natural alkaloid, noscapine, for repurposing against the main protease of SARS-CoV-2, a key enzyme involved in its reproduction. We performed the molecular dynamics (MD) simulation in an explicit solvent to investigate the molecular mechanisms of noscapine for stable binding and conformational changes to the main protease (Mpro) of SARS-CoV-2. The drug repurposing study revealed the high potential of noscapine and proximal binding to the Mpro enzyme in a comparative binding pattern analyzed with chloroquine, ribavirin, and favipiravir. Noscapine binds closely to binding pocket-3 of the Mpro enzyme and depicted stable binding with RMSD 0.1-1.9 Å and RMSF profile peak conformational fluctuations at 202-306 residues, and a Rg score ranging from 21.9 to 22.4 Å. The MM/PB (GB) SA calculation landscape revealed the most significant contribution in terms of binding energy with ΔPB -19.08 and ΔGB -27.17 kcal/mol. The electrostatic energy distribution in MM energy was obtained to be -71.16 kcal/mol and depicted high free energy decomposition (electrostatic energy) at 155-306 residues (binding pocket-3) of Mpro by a MM force field. Moreover, the dynamical residue cross-correlation map also stated that the high pairwise correlation occurred at binding residues 200-306 of the Mpro enzyme (binding pocket-3) with noscapine. Principal component analysis depicted the enhanced movement of protein atoms with a high number of static hydrogen bonds. The obtained binding results of noscapine were also well correlated with the pharmacokinetic parameters of antiviral drugs.

Exploring the energetic basis of binding of currently used drugs against HIV-1 subtype CRF01_AE protease via molecular dynamics simulations

Non-B strains cause nearly 90% of the worldwide human immunodeficiency virus (HIV) infections. At the same time, the protease inhibitors (PIs) were designed for subtype B. Therefore, the use of PIs in the non-B subtype context requires further investigation. Herein, we have investigated the effectiveness of currently used four PIs, namely atazanavir, darunavir, lopinavir, and tipranavir against subtype CRF01_AE (PRCRF) by employing the MD/MMPBSA (molecular dynamics/molecular mechanics Poisson-Boltzmann surface area) scheme. Our investigation reveals that tipranavir is the most potent inhibitor against PRCRF while the other three PIs display a similar binding affinity. The energetic penalty arises due to the desolvation of polar groups always disfavor the association between PRCRF and PI, and this contribution is the least in the case of tipranavir/PRCRF compared to the other three PI-PRCRF complexes resulting in a better binding affinity for tipranavir. Further, it is revealed that the primary interaction controlling the binding of inhibitors with PRCRF is the van der Waals forces. The dynamic cross-correlation map and principal component analysis show that the anti-correlated motion at the flap region of PRCRF is diminished after the ligand binding. Further, our studies indicate that D25' forms a stable H-bond with darunavir, lopinavir, and tipranavir, while D25 forms a stable H-bond with atazanavir. The per-residue based decomposition of free energy reveals the actual residual origin of the binding free energy and identify the hotspot residues. Overall, the data presented in this study can guide the computer-aided rational design of more potent drugs targetting HIV-1 PRCRF. Communicated by Ramaswamy H. Sarma

Computation-aided engineering of starch-debranching pullulanase from Bacillus thermoleovorans for enhanced thermostability.

Pullulanases are widely used in food, medicine, and other industries because they specifically hydrolyze α-1,6-glycosidic linkages in starch and oligosaccharides. In addition, high-temperature thermostable pullulanase has multiple advantages, including decreasing saccharification solution viscosity accompanied with enhanced mass transfer and reducing microbial contamination in starch hydrolysis. However, thermophilic pullulanase availability remains limited. Additionally, most do not meet starch-manufacturing requirements due to weak thermostability. Here, we developed a computation-aided strategy to engineer the thermophilic pullulanase from Bacillus thermoleovorans. First, three computational design predictors (FoldX, I-Mutant 3.0, and dDFIRE) were combined to predict stability changes introduced by mutations. After excluding conserved and catalytic sites, 17 mutants were identified. After further experimental verification, we confirmed six positive mutants. Among them, the G692M mutant had the highest thermostability improvement, with 3.8°C increased Tm and 2.1-fold longer half-life than the wild type at 70°C. We then characterized the mechanism underlying increased thermostability, such as rigidity enhancement, closer conformation, and strengthened motion correlation using root mean square fluctuation (RMSF), principal component analysis (PCA), dynamic cross-correlation map (DCCM), and free energy landscape (FEL) analysis. KEY POINTS: • A computation-aided strategy was developed to engineer pullulanase thermostability. • Seventeen mutants were identified by combining three computational design predictors. • The G692M mutant was obtained with increased Tmand half-life at 70°C.

Correlated Motions and Dynamics in Different Domains of Epidermal Growth Factor Receptor With L858R and T790M Mutations.

Non-small cell lung cancer with an activating epidermal growth factor receptor (EGFR) mutation responds well to targeted drugs. In most cases, drug resistance appears after about a year. Several studies have been conducted on the kinase domain of EGFR to understand the drug resistance mechanism. Since EGFR is a multi-domain protein, mutation in the kinase domain may affect the other domains as well. In this study, we examine the complete structure of the multi-domain EGFR protein and its mutants. We performed molecular dynamics simulations for wildtype EGFR, EGFR with L858R mutation, and EGFR with L858R and T790M mutations. We applied normal mode analysis and complex network analysis to extract the correlated motions in the domains of EGFR. The normal modes are used to construct the dynamic cross-correlation map (DCCM). Simulation results show different patterns of correlated motions in each domain of EGFR mutants compared to the wildtype. In Domains 1 and 3 of the extracellular region, a small number of weak positively correlated motions are extracted. Domains 2 and 4 show large numbers of both positive and negative motions. However, the negatively correlated motions are stronger in mutant structures compared to the wildtype. In Domain 7, some residues showed a positive correlation around the main diagonal. We also identified different communities, nodes and crucial residues in the domains of the structures, which can be important for the function of EGFR. Moreover, hydrogen bond analysis is performed for the stability analysis. The mutant structures have fewer hydrogen bonds compared to the wildtype. Overall, these findings are useful for understanding the dynamics and communications in EGFR domains.

In-silico mutational study of ferulic acid decarboxylase for improvement of substrate binding empathy

Biotransformation of ferulic acid by microorganisms provides a better alternative for production of flavour and fragrance compounds like 4-vinylguaiacol and vanillin. Ferulic acid is transformed to 4-vinylguaiacol using the non-oxidative decarboxylation pathway by ferulic acid decarboxylase (FADase). Here we report, computational mutational analysis of active site of FADase. Site directed mutations (single nucleotide polymorphisms, SNPs) were commenced using in-silico molecular modelling methods. Energy minimisation, dynamic cross-correlation map (DCCM) and principle components analysis (PCA) methods were subsequently applied to validate different conformers (SNPs) of FADase. Substrate ferulic acid was docked with different SNPs. It was observed that, certain amino acids like Tyr21, Trp25, Tyr27 and Glu134 at active sites are responsible for better binding to ferulic acid. Further, mutated form Y27F (Tyr27Phe) of FADase shows a better binding affinity towards ferulic acid than its native form through structure analysis and docking studies.

Exploring the effect of N308D mutation on protein tyrosine phosphatase-2 cause gain-of-function activity by a molecular dynamics study.

One of the most common protein tyrosine phosphatase-2 (SHP2) mutations in Noonan syndrome is the N308D mutation, and it increases the activity of the protein. However, the molecular basis of the activation of N308D mutation on SHP2 conformations is poorly understood. Here, molecular dynamic simulations were performed on SHP2 and SHP2-N308D to explore the effect of N308D mutation on SHP2 cause gain of function activity, respectively. The principal component analysis,dynamic cross-correlation map, secondary structure analysis, residue interaction networks, and solvent accessible surface area analysis suggested that the N308D mutation distorted the residues interactions network between the allosteric site (residue Gly244-Gly246) and C-SH2 domain, including the hydrogen bond formation and the binding energy. Meanwhile, the activity of catalytic site (residue Gly503-Val505) located in the Q-loop in mutant increased due to this region's high fluctuations. Therefore, the substrate had more chances to access to the catalytic activity site of the precision time protocol domain of SHP2-N308D, which was easy to be exposed. In addition, we had speculated that the Lys244 located in the allosteric site was the key residue which lead to the protein conformation changes. Consequently, overall calculations presented in this study ultimately provide a useful understanding of the increased activity of SHP2 caused by the N308D mutation.

Molecular Mechanism Behind the Resistance of the G1202R-Mutated Anaplastic Lymphoma Kinase to the Approved Drug Ceritinib.

Anaplastic lymphoma kinase (ALK) has been regarded as an essential target for the treatment of nonsmall cell lung cancer (NSCLC). However, the emergence of the G1202R solvent front mutation that confers resistance to the drugs was reported for the first as well as the second generation ALK inhibitors. It was thought that the G1202R solvent front mutation might hinder the drug binding. In this study, a different fact could be clarified by multiple molecular modeling methodologies through a structural analogue of ceritinib (compound 10, Cpd-10) that is reported to be a potent inhibitor against the G1202R mutation. Herein, molecular docking, accelerated molecular dynamics (aMD) simulations in conjunction with principal component analysis (PCA), and free energy map calculations were used to produce reasonable and representative initial conformations for the conventional MD simulations. Compared with Cpd-10, the binding specificity of ceritinib between ALK wild-type (ALKWT) and ALK G1202R (ALKG1202R) are primarily controlled by the conformational change of the P-loop- and A-loop-induced energetic redistributions, and the variation is nonpolar interactions, as indicated by conventional MD simulations, PCA, dynamic cross-correlation map (DCCM) analysis, and free energy calculations. Furthermore, the umbrella sampling (US) simulations were carried out to make clear the principle of the dissociation processes of ceritinib and Cpd-10 toward ALKWT and ALKG1202R. The calculation results suggest that Cpd-10 has similar dissociation processes from both ALKWT and ALKG1202R, but ceritinib is more easily dissociated from ALKG1202R than from ALKWT, thus less residence time is responsible for the ceritinib resistance. Our results suggest that both the binding specificity and the drug residence time should be emphasized in rational drug design to overcome the G1202R solvent front mutation of ALK resistance.