Intersection of network medicine and machine learning towards investigating the key biomarkers and pathways underlying amyotrophic lateral sclerosis: a systematic review.

BACKGROUND: Network medicine is an emerging area of research that focuses on delving into the molecular complexity of the disease, leading to the discovery of network biomarkers and therapeutic target discovery. Amyotrophic lateral sclerosis (ALS) is a complicated rare disease with unknown pathogenesis and no available treatment. In ALS, network properties appear to be potential biomarkers that can be beneficial in disease-related applications when explored independently or in tandem with machine learning (ML) techniques. OBJECTIVE: This systematic literature review explores recent trends in network medicine and implementations of network-based ML algorithms in ALS. We aim to provide an overview of the identified primary studies and gather details on identifying the potential biomarkers and delineated pathways. METHODS: The current study consists of searching for and investigating primary studies from PubMed and Dimensions.ai, published between 2018 and 2022 that reported network medicine perspectives and the coupling of ML techniques. Each abstract and full-text study was individually evaluated, and the relevant studies were finally included in the review for discussion once they met the inclusion and exclusion criteria. RESULTS: We identified 109 eligible publications from primary studies representing this systematic review. The data coalesced into two themes: application of network science to identify disease modules and promising biomarkers in ALS, along with network-based ML approaches. Conclusion This systematic review gives an overview of the network medicine approaches and implementations of network-based ML algorithms in ALS to determine new disease genes, and identify critical pathways and therapeutic target discovery for personalized treatment.

Visual and cognitive processes contribute to age-related improvements in visual selective attention.

Children (N = 103, 4-9 years, 59 females, 84% White, c. 2019) completed visual processing, visual feature integration (color, luminance, motion), and visual search tasks. Contrast sensitivity and feature search improved with age similarly for luminance and color-defined targets. Incidental feature integration improved more with age for color-motion than luminance-motion. Individual differences in feature search ( ß = .11) and incidental feature integration ( ß = .06) mediated age-related changes in conjunction visual search, an index of visual selective attention. These findings suggest that visual selective attention is best conceptualized as a series of developmental trajectories, within an individual, that vary by an object's defining features. These data have implications for design of educational and interventional strategies intended to maximize attention for learning and memory.

Identifying the natural polyphenol catechin as a multi-targeted agent against SARS-CoV-2 for the plausible therapy of COVID-19: an integrated computational approach.

The global pandemic crisis, coronavirus disease 2019 (COVID-19), caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has claimed the lives of millions of people across the world. Development and testing of anti-SARS-CoV-2 drugs or vaccines have not turned to be realistic within the timeframe needed to combat this pandemic. Here, we report a comprehensive computational approach to identify the multi-targeted drug molecules against the SARS-CoV-2 proteins, whichare crucially involved in the viral-host interaction, replication of the virus inside the host, disease progression and transmission of coronavirus infection. Virtual screening of 75 FDA-approved potential antiviral drugs against the target proteins, spike (S) glycoprotein, human angiotensin-converting enzyme 2 (hACE2), 3-chymotrypsin-like cysteine protease (3CLpro), cathepsin L (CTSL), nucleocapsid protein, RNA-dependent RNA polymerase (RdRp) and non-structural protein 6 (NSP6), resulted in the selection of seven drugs which preferentially bind to the target proteins. Further, the molecular interactions determined by molecular dynamics simulation revealed that among the 75 drug molecules, catechin can effectively bind to 3CLpro, CTSL, RBD of S protein, NSP6 and nucleocapsid protein. It is more conveniently involved in key molecular interactions, showing binding free energy (ΔGbind) in the range of -5.09 kcal/mol (CTSL) to -26.09 kcal/mol (NSP6). At the binding pocket, catechin is majorly stabilized by the hydrophobic interactions, displays ΔEvdW values: -7.59 to -37.39 kcal/mol. Thus, the structural insights of better binding affinity and favorable molecular interaction of catechin toward multiple target proteins signify that catechin can be potentially explored as a multi-targeted agent against COVID-19.

Predicting children's math skills from task-based and resting-state functional brain connectivity.

A critical goal of cognitive neuroscience is to predict behavior from neural structure and function, thereby providing crucial insights into who might benefit from clinical and/or educational interventions. Across development, the strength of functional connectivity among a distributed set of brain regions is associated with children's math skills. Therefore, in the present study we use connectome-based predictive modeling to investigate whether functional connectivity during numerical processing and at rest "predicts" children's math skills (N = 31, Mage = 9.21 years, 14 Female). Overall, we found that functional connectivity during symbolic number comparison and rest, but not during nonsymbolic number comparison, predicts children's math skills. Each task revealed a largely distinct set of predictive connections distributed across canonical brain networks and major brain lobes. Most of these predictive connections were negatively correlated with children's math skills so that weaker connectivity predicted better math skills. Notably, these predictive connections were largely nonoverlapping across task states, suggesting children's math abilities may depend on state-dependent patterns of network segregation and/or regional specialization. Furthermore, the current predictive modeling approach moves beyond brain-behavior correlations and toward building models of brain connectivity that may eventually aid in predicting future math skills.

Genome-wide analysis of PTR transporters in Candida species and their functional characterization in Candida auris.

The peptide transport (PTR) or proton-dependent oligopeptide transporter (POT) family exploits the inwardly directed proton motive force to facilitate the cellular uptake of di/tripeptides. Interestingly, some representatives are also shown to import peptide-based antifungals in certain Candida species. Thus, the identification and characterization of PTR transporters serve as an essential first step for their potential usage as antifungal peptide uptake systems. Herein, we present a genome-wide inventory of the PTR transporters in five prominent Candida species. Our study identifies 2 PTR transporters each in C. albicans and C. dubliniensis, 1 in C. glabrata, 4 in C. parapsilosis, and 3 in C. auris. Notably, despite all representatives retaining the conserved features seen in the PTR family, there exist two distinct classes of PTR transporters that differ in terms of their sequence identities and lengths of certain extracellular and intracellular segments. Further, we also evaluated the contribution of each PTR protein of the newly emerged multi-drug-resistant C. auris in di/tripeptide uptake. Notably, deletion of two PTR genes BNJ08_003830 and BNJ08_005124 led to a marked reduction in the transport capabilities of several tested di/tripeptides. However, all three genes could complement the role of native PTR2 gene of Saccharomyces cerevisiae, albeit to varied levels. Besides, BNJ08_005124 deletion also resulted in increased resistance toward the peptide-nucleoside drug Nikkomycin Z as well as the glucosamine-6-phosphate synthase inhibitor, L-norvalyl-N3-(4-methoxyfumaroyl)-L-2,3-diaminopropionoic acid (Nva-FMDP), pointing toward its predominant role in their uptake mechanism. Altogether, the study provides an important template for future structure-function investigations of PTR transporters in Candida species. KEY POINTS: • Candida genome encodes for two distinct classes of PTR transporters. • Candida auris encodes for 3 PTR transporters with different specificities. • BNJ08_005124 in C. auris is involved in the uptake of Nikkomycin Z and Nva-FMDP.

Genomic landscape of the DHA1 family in Candida auris and mapping substrate repertoire of CauMdr1.

The last decade has witnessed the rise of an extremely threatening healthcare-associated multidrug-resistant non-albicans Candida (NAC) species, Candida auris. Since besides target alterations, efflux mechanisms contribute maximally to antifungal resistance, it is imperative to investigate their contributions in this pathogen. Of note, within the major facilitator superfamily (MFS) of efflux pumps, drug/H+ antiporter family 1 (DHA1) has been established as a predominant contributor towards xenobiotic efflux. Our study provides a complete landscape of DHA1 transporters encoded in the genome of C. auris. This study identifies 14 DHA1 transporters encoded in the genome of the pathogen. We also construct deletion and heterologous overexpression strains for the most important DHA1 drug transporter, viz., CauMdr1 to map the spectrum of its substrates. While the knockout strain did not show any significant changes in the resistance patterns against most of the tested substrates, the ortholog when overexpressed in a minimal background Saccharomyces cerevisiae strain, AD1-8u-, showed significant enhancement in the minimum inhibitory concentrations (MICs) against a large panel of antifungal molecules. Altogether, the present study provides a comprehensive template for investigating the role of DHA1 members of C. auris in antifungal resistance mechanisms. KEY POINTS: • Fourteen putative DHA1 transporters are encoded in the Candida auris genome. • Deletion of the CauMDR1 gene does not lead to major changes in drug resistance. • CauMdr1 recognizes and effluxes numerous xenobiotics, including prominent azoles.

Implementation of homology based and non-homology based computational methods for the identification and annotation of orphan enzymes: using Mycobacterium tuberculosis H37Rv as a case study.

BACKGROUND: Homology based methods are one of the most important and widely used approaches for functional annotation of high-throughput microbial genome data. A major limitation of these methods is the absence of well-characterized sequences for certain functions. The non-homology methods based on the context and the interactions of a protein are very useful for identifying missing metabolic activities and functional annotation in the absence of significant sequence similarity. In the current work, we employ both homology and context-based methods, incrementally, to identify local holes and chokepoints, whose presence in the Mycobacterium tuberculosis genome is indicated based on its interaction with known proteins in a metabolic network context, but have not been annotated. We have developed two computational procedures using network theory to identify orphan enzymes ('Hole finding protocol') coupled with the identification of candidate proteins for the predicted orphan enzyme ('Hole filling protocol'). We propose an integrated interaction score based on scores from the STRING database to identify candidate protein sequences for the orphan enzymes from M. tuberculosis, as a case study, which are most likely to perform the missing function. RESULTS: The application of an automated homology-based enzyme identification protocol, ModEnzA, on M. tuberculosis genome yielded 56 novel enzyme predictions. We further predicted 74 putative local holes, 6 choke points, and 3 high confidence local holes in the genome using 'Hole finding protocol'. The 'Hole-filling protocol' was validated on the E. coli genome using artificial in-silico enzyme knockouts where our method showed 25% increased accuracy, compared to other methods, in assigning the correct sequence for the knocked-out enzyme amongst the top 10 ranks. The method was further validated on 8 additional genomes. CONCLUSIONS: We have developed methods that can be generalized to augment homology-based annotation to identify missing enzyme coding genes and to predict a candidate protein for them. For pathogens such as M. tuberculosis, this work holds significance in terms of increasing the protein repertoire and thereby, the potential for identifying novel drug targets.

Representational similarity analysis reveals atypical age-related changes in brain regions supporting face and car recognition in autism.

BACKGROUND: Autism Spectrum Disorder (ASD) is associated with atypical activation in the ventral stream during face processing. The current study further characterizes the development of face processing in ASD using a multivoxel pattern analysis, which assesses the similarity in the representation of exemplars from the same category. METHODS: Ninety-two children, adolescents and adults - with and without ASD - performed the Cambridge Face Memory Test, the Australian Face Memory Test, and a matched car memory test. Regions of interest during these tasks included Fusiform Face Area (FFA), based on the literature, and additional, structurally-defined regions in the ventral stream. Group differences in the patterns of activity within these ROIs when memorizing exemplars were examined using a representational similarity analysis (RSA). RESULTS: The RSA revealed significant interactions between age group and diagnostic group in R FFA, with increasing similarity within a category (faces, cars) into adulthood typically but not in those with ASD. This pattern was also evident in structurally defined ventral stream regions, namely L inferior frontal gyrus (IFG), bilateral temporoparietal junction (TPJ), L inferior temporal lobule, and the R fusiform gyrus. CONCLUSIONS: The specialization of face and object processing from adolescence to adulthood evident in typical development may be impaired in ASD, undermining the ability to reach adult-level visual processing in those with ASD.

Pitchers of Nepenthes khasiana express several digestive-enzyme encoding genes, harbor mostly fungi and probably evolved through changes in the expression of leaf polarity genes.

BACKGROUND: A structural phenomenon seen in certain lineages of angiosperms that has captivated many scholars including Charles Darwin is the evolution of plant carnivory. Evidently, these structural features collectively termed carnivorous syndrome, evolved to aid nutritional acquisition from attracted, captured and digested prey. We now understand why plant carnivory evolved but how carnivorous plants acquired these attributes remains a mystery. In an attempt to understand the evolution of Nepenthes pitcher and to shed more light on its role in prey digestion, we analyzed the transcriptome data of the highly specialized Nepenthes khasiana leaf comprising the leaf base lamina, tendril and the different parts/zones of the pitcher tube viz. digestive zone, waxy zone and lid. RESULTS: In total, we generated around 262 million high-quality Illumina reads. Reads were pooled, normalized and de novo assembled to generate a reference transcriptome of about 412,224 transcripts. We then estimated transcript abundance along the N. khasiana leaf by mapping individual reads from each part/zone to the reference transcriptome. Correlation-based hierarchical clustering analysis of 27,208 commonly expressed genes indicated functional relationship and similar cellular processes underlying the development of the leaf base and the pitcher, thereby implying that the Nepenthes pitcher is indeed a modified leaf. From a list of 2386 differentially expressed genes (DEGs), we identified transcripts encoding key enzymes involved in prey digestion and protection against pathogen attack, some of which are expressed at high levels in the digestive zone. Interestingly, many of these enzyme-encoding genes are also expressed in the unopened N. khasiana pitcher. Transcripts showing homology to both bacteria and fungi were also detected; and in the digestive zone, fungi are more predominant as compared to bacteria. Taking cues from histology and scanning electron microscopy (SEM) photomicrographs, we found altered expressions of key regulatory genes involved in leaf development. Of particular interest, the expression of class III HOMEODOMAIN-LEUCINE ZIPPER (HD-ZIPIII) and ARGONAUTE (AGO) genes were upregulated in the tendril. CONCLUSIONS: Our findings suggest that N. khasiana pitchers employ a wide range of enzymes for prey digestion and plant defense, harbor microbes and probably evolved through altered expression of leaf polarity genes.

What underlies visual selective attention development? Evidence that age-related improvements in visual feature integration influence visual selective attention performance.

Visual selective attention (VSA) improves across childhood. Conjunction search tasks require integrating multiple visual features in order to find a target among distractors and are often used to measure VSA. Motivated by the visual system's architecture and developmental changes in neural connectivity, we predicted that feature integration across separate visual pathways (e.g., color and motion) should develop later than feature integration within the same visual pathways (e.g., luminance and motion). A total of 89 4- to 10-year-old children completed a visual search task that manipulated whether feature integration was between separate parallel visual pathways or within the same visual pathway. We first examined whether color-motion integration was associated with a performance cost relative to luminance-motion integration across childhood. We found that color-motion integration was worse than luminance-motion integration in early childhood but that this difference decreased with age. We also examined whether luminance-motion and color-motion visual search performance developed differently across childhood. Reaction time (RT) visual search slopes for the luminance-motion condition were both stable across childhood and steeper overall than those for the color-motion condition. In contrast, RT search slopes for the color-motion condition became steeperincrease across childhood. Finally, we found that age-related improvements in color-motion integration, relative to luminance-motion integration, were associated with longer color-motion search rates across childhood. These data suggest that age-related improvements in color-motion feature integration may increase competition between color-motion targets and distractors, thereby increasing the amount of time needed to process distractors as nontargets during the selection process.

GCAC: galaxy workflow system for predictive model building for virtual screening.

BACKGROUND: Traditional drug discovery approaches are time-consuming, tedious and expensive. Identifying a potential drug-like molecule using high throughput screening (HTS) with high confidence is always a challenging task in drug discovery and cheminformatics. A small percentage of molecules that pass the clinical trial phases receives FDA approval. This whole process takes 10-12 years and millions of dollar of investment. The inconsistency in HTS is also a challenge for reproducible results. Reproducible research in computational research is highly desirable as a measure to evaluate scientific claims and published findings. This paper describes the development and availability of a knowledge based predictive model building system using the R Statistical Computing Environment and its ensured reproducibility using Galaxy workflow system. RESULTS: We describe a web-enabled data mining analysis pipeline which employs reproducible research approaches to confront the issue of availability of tools in high throughput virtual screening. The pipeline, named as "Galaxy for Compound Activity Classification (GCAC)" includes descriptor calculation, feature selection, model building, and screening to extract potent candidates, by leveraging the combined capabilities of R statistical packages and literate programming tools contained within a workflow system environment with automated configuration. CONCLUSION: GCAC can serve as a standard for screening drug candidates using predictive model building under galaxy environment, allowing for easy installation and reproducibility. A demo site of the tool is available at http://ccbb.jnu.ac.in/gcac.

Information theoretic measures and mutagenesis identify a novel linchpin residue involved in substrate selection within the nucleotide-binding domain of an ABCG family exporter Cdr1p.

ABC transporters are membrane-bound pumps composed of two major domains: the transmembrane domain(s) (TMDs) and the nucleotide-binding domain(s) (NBDs). Sequence analyses of the NBDs of key ABC exporters revealed a residue position within the H-loop to be differentially conserved in the ABCG family, wherein there lies glutamine instead of positively charged arginine/lysine as in non-ABCG members. Consequently, contrasting NBD sequences of fungal Pleiotropic Drug Resistance transporters (PDR/ABCG) with that of Cholesterol/Phospholipid and Retinal (CPR/ABCA) Flippase family revealed a high Cumulative Relative Entropy (CRE) score of this residue position implying its family-specific functional significance. Further, substitution of the glutamine by arginine in both the NBDs of a representative PDR/ABCG member, (Candida drug resistance 1 protein) Cdr1p led to selective susceptibility of the Saccharomyces cerevisiae strains overexpressing the corresponding mutant proteins (Q362R and Q1060R) towards antifungal substrates without any impact on the ATPase activity. Consistent with the findings from previous studies on H-loop motif of fungal PDR transporters, the current report points towards a role of the glutamine residue within both canonical and divergent H-loop of Cdr1p in conferring substrate selection in a precisely identical manner.

TFE-induced local unfolding and fibrillation of SOD1: bridging the experiment and simulation studies.

Misfolding and aggregation of Cu, Zn Superoxide dismutase (SOD1) is involved in the neurodegenerative disease, amyotrophic lateral sclerosis. Many studies have shown that metal-depleted, monomeric form of SOD1 displays substantial local unfolding dynamics and is the precursor for aggregation. Here, we have studied the structure and dynamics of different apo monomeric SOD1 variants associated with unfolding and aggregation in aqueous trifluoroethanol (TFE) through experiments and simulation. TFE induces partially unfolded ß-sheet-rich extended conformations in these SOD1 variants, which subsequently develops aggregates with fibril-like characteristics. Fibrillation was achieved more easily in disulfide-reduced monomeric SOD1 when compared with wild-type and mutant monomeric SOD1. At higher concentrations of TFE, a native-like structure with the increase in α-helical content was observed. The molecular dynamics simulation results illustrate distinct structural dynamics for different regions of SOD1 variants and show uniform local unfolding of ß-strands. The strands protected by the zinc-binding and electrostatic loops were found to unfold first in 20% (v/v) TFE, leading to a partial unfolding of ß-strands 4, 5, and 6 which are prone to aggregation. Our results thus shed light on the role of local unfolding and conformational dynamics in SOD1 misfolding and aggregation.

The emergence of object-based visual attention in infancy: A role for family socioeconomic status and competing visual features.

The development of spatial visual attention has been extensively studied in infants, but far less is known about the emergence of object-based visual attention. We tested 3-5- and 9-12-month-old infants on a task that allowed us to measure infants' attention orienting bias toward whole objects when they competed with color, motion, and orientation feature information. Infants' attention orienting to whole objects was affected by the dimension of the competing visual feature. Whether attention was biased toward the whole object or its salient competing feature (e.g., "ball" or "red") changed with age for the color feature, with infants biased toward whole objects with age. Moreover, family socioeconomic status predicted feature-based attention in the youngest infants and object-based attention in the older infants when color feature information competed with whole-object information.

Exploring the interaction between Mycobacterium tuberculosis enolase and human plasminogen using computational methods and experimental techniques.

Surface localized microbial enolases' binding with human plasminogen has been increasingly proven to have an important role in initial infection cycle of several human pathogens. Likewise, surface localized Mycobacterium tuberculosis (Mtb) enolase also binds to human plasminogen, and this interaction may entail crucial consequences for granuloma stability. The current study is the first attempt to explore the plasminogen interacting residues of enolase from Mtb. Beginning with the structural modeling of Mtb enolase, the binding pose of Mtb enolase and human plasminogen was predicted using protein-protein docking simulations. The binding pose revealed the interface region with interacting residues and molecular interactions. Next, the interacting residues were refined and ranked by using various criteria. Finally, the selected interacting residues were tested experimentally for their involvement in plasminogen binding. The two consecutive lysine residues, Lys-193 and Lys-194, turned out to be active residues for plasminogen binding. These residues when substituted for alanine along with the most active residue Lys-429, that is, the triple mutant (K193A + K194A + K429A) Mtb enolase, exhibited 40% reduction in plasminogen binding. It is worth noting that Mtb enolase lost nearly half of the plasminogen binding activity with only three simultaneous substitutions, without any significant secondary structure perturbation. Further, the sequence comparison between Mtb and human enolase isoforms suggests the possibility of selective targeting of Mtb enolase to obstruct binding of human plasminogen.

Alterations in local stability and dynamics of A4V SOD1 in the presence of trifluoroethanol.

Alterations in the local dynamics of Cu/Zn Superoxide dismutase (SOD1) due to mutations affect the protein folding, stability, and function leading to misfolding and aggregation seen in amyotrophic lateral sclerosis (ALS). Here, we study the structure and dynamics of the most devastating ALS mutation, A4V SOD1 in aqueous trifluoroethanol (TFE) through experiments and simulation. Far-UV circular dichroism (CD) studies shows that TFE at intermediate concentrations (∼15% - 30%) induce partially unfolded ß-sheet-rich extended conformations in A4V SOD1 which subsequently aggregates. Molecular dynamics (MD) simulation results shows that A4V SOD1 increases local dynamics in the active site loops that leads to the destabilization of the ß-barrel and loss of hydrophobic contacts, thus stipulating a basis for aggregation. Free energy landscape (FEL) and essential dynamics (ED) analysis demonstrates the conformational heterogeneity in A4V SOD1. Our results thus shed light on the role of local unfolding and conformational dynamics in aggregation of SOD1.

Functional connectivity differences in autism during face and car recognition: underconnectivity and atypical age-related changes.

Face recognition abilities improve between adolescence and adulthood over typical development (TD), but plateau in autism, leading to increasing face recognition deficits in autism later in life. Developmental differences between autism and TD may reflect changes between neural systems involved in the development of face encoding and recognition. Here, we focused on whole-brain connectivity with the fusiform face area (FFA), a well-established face-preferential brain region. Older children, adolescents, and adults with and without autism completed the Cambridge Face Memory Test, and a matched car memory test, during fMRI scanning. We then examined task-based functional connectivity between the FFA and the rest of the brain, comparing autism and TD groups during encoding and recognition of face and car stimuli. The autism group exhibited underconnectivity, relative to the TD group, between the FFA and frontal and primary visual cortices, independent of age. Underconnectivity with the medial and rostral lateral prefrontal cortex was face-specific during encoding and recognition, respectively. Conversely, underconnectivity with the L orbitofrontal cortex was evident for both face and car encoding. Atypical age-related changes in connectivity emerged between the FFA and the R temporoparietal junction, and R dorsal striatum for face stimuli only. Similar differences in age-related changes in autism emerged for FFA connectivity with the amygdala across both face and car recognition. Thus, underconnectivity and atypical development of functional connectivity may lead to a less optimal face-processing network in the context of increasing general and social cognitive deficits in autism.

Engineering Nucleotide Specificity of Succinyl-CoA Synthetase in Blastocystis: The Emerging Role of Gatekeeper Residues.

Charged, solvent-exposed residues at the entrance to the substrate binding site (gatekeeper residues) produce electrostatic dipole interactions with approaching substrates, and control their access by a novel mechanism called "electrostatic gatekeeper effect". This proof-of-concept study demonstrates that the nucleotide specificity can be engineered by altering the electrostatic properties of the gatekeeper residues outside the binding site. Using Blastocystis succinyl-CoA synthetase (SCS, EC 6.2.1.5), we demonstrated that the gatekeeper mutant (ED) resulted in ATP-specific SCS to show high GTP specificity. Moreover, nucleotide binding site mutant (LF) had no effect on GTP specificity and remained ATP-specific. However, via combination of the gatekeeper mutant with the nucleotide binding site mutant (ED+LF), a complete reversal of nucleotide specificity was obtained with GTP, but no detectable activity was obtained with ATP. This striking result of the combined mutant (ED+LF) was due to two changes; negatively charged gatekeeper residues (ED) favored GTP access, and nucleotide binding site residues (LF) altered ATP binding, which was consistent with the hypothesis of the "electrostatic gatekeeper effect". These results were further supported by molecular modeling and simulation studies. Hence, it is imperative to extend the strategy of the gatekeeper effect in a different range of crucial enzymes (synthetases, kinases, and transferases) to engineer substrate specificity for various industrial applications and substrate-based drug design.

Molecular modeling and simulation studies of recombinant laccase from Yersinia enterocolitica suggests significant role in the biotransformation of non-steroidal anti-inflammatory drugs.

The YacK gene from Yersinia enterocolitica strain 7, cloned in pET28a vector and expressed in Escherichia coli BL21 (DE3), showed laccase activity when oxidized with 2,2'-azino-bis(3-ethylbenzthiazoline-6-sulfonic acid) (ABTS) and guaiacol. The recombinant laccase protein was purified and characterized biochemically with a molecular mass of ≈58 KDa on SDS-PAGE and showed positive zymogram with ABTS. The protein was highly robust with optimum pH 9.0 and stable at 70 °C upto 12 h with residual activity of 70%. Kinetic constants, Km values, for ABTS and guaiacol were 675 µM and 2070 µM, respectively, with corresponding Vmax values of 0.125 µmol/ml/min and 6500 µmol/ml/min. It also possess antioxidative property against BSA and Cu(2+)/H2O2 model system. Constant pH MD simulation studies at different protonation states of the system showed ABTS to be most stable at acidic pH, whereas, diclofenac at neutral pH. Interestingly, aspirin drifted out of the binding pocket at acidic and neutral pH, but showed stable binding at alkaline pH. The biotransformation of diclofenac and aspirin by laccase also corroborated the in silico results. This is the first report on biotransformation of non-steroidal anti-inflammatory drugs (NSAIDs) using recombinant laccase from gut bacteria, supported by in silico simulation studies.