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.

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.

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.

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.

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.

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.

Socio-economic, epidemiological and geographic features based on GIS-integrated mapping to identify malarial hotspots.

BACKGROUND: Malaria is a major health problem in the tropical and subtropical world. In India, 95% of the population resides in malaria endemic regions and it is major public health problem in most parts of the country. The present work has developed malaria maps by integrating socio-economic, epidemiology and geographical dimensions of three eastern districts of Uttar Pradesh, India. The area has been studied in each dimension separately, and later integrated to find a list of vulnerable pockets/villages, called as malarial hotspots. METHODS: The study has been done at village level. Seasonal variation of malaria, comparison of epidemiology indices and progress of the medical facility were studied. Ten independent geographical information system (GIS) maps of socio-economic aspects (population, child population, literacy, and work force participation), epidemiology (annual parasitic index (API) and slides collected and examined) and geographical features (settlement, forest cover, water bodies, rainfall, relative humidity, and temperature) were drawn and studied. These maps were overlaid based on computed weight matrix to find malarial hotspot. RESULTS: It was found that the studied dimensions were inter-weaving factors for malaria epidemic and closely affected malaria situations as evidenced from the obtained correlation matrix. The regions with water logging, high rainfall and proximity to forest, along with poor socio-economic conditions, are primarily hotspot regions. The work is presented through a series of GIS maps, tables, figures and graphs. A total of 2,054 out of 8,973 villages studied were found to be malarial hotspots and consequently suggestions were made to the concerned government malaria offices. CONCLUSION: With developing technology, information tools such as GIS, have captured almost every field of scientific research especially of vector-borne diseases, such as malaria. Malarial mapping enables easy update of information and effortless accessibility of geo-referenced data to policy makers to produce cost-effective measures for malaria control in endemic regions.

Insight into pleiotropic drug resistance ATP-binding cassette pump drug transport through mutagenesis of Cdr1p transmembrane domains.

The fungal ATP-binding cassette (ABC) transporter Cdr1 protein (Cdr1p), responsible for clinically significant drug resistance, is composed of two transmembrane domains (TMDs) and two nucleotide binding domains (NBDs). We have probed the nature of the drug binding pocket by performing systematic mutagenesis of the primary sequences of the 12 transmembrane segments (TMSs) found in the TMDs. All mutated proteins were expressed equally well and localized properly at the plasma membrane in the heterologous host Saccharomyces cerevisiae, but some variants differed significantly in efflux activity, substrate specificity, and coupled ATPase activity. Replacement of the majority of the amino acid residues with alanine or glycine yielded neutral mutations, but about 42% of the variants lost resistance to drug efflux substrates completely or selectively. A predicted three-dimensional homology model shows that all the TMSs, apart from TMS4 and TMS10, interact directly with the drug-binding cavity in both the open and closed Cdr1p conformations. However, TMS4 and TMS10 mutations can also induce total or selective drug susceptibility. Functional data and homology modeling assisted identification of critical amino acids within a drug-binding cavity that, upon mutation, abolished resistance to all drugs tested singly or in combinations. The open and closed Cdr1p models enabled the identification of amino acid residues that bordered a drug-binding cavity dominated by hydrophobic residues. The disposition of TMD residues with differential effects on drug binding and transport are consistent with a large polyspecific drug binding pocket in this yeast multidrug transporter.

Rationally designed transmembrane peptide mimics of the multidrug transporter protein Cdr1 act as antagonists to selectively block drug efflux and chemosensitize azole-resistant clinical isolates of Candida albicans.

Drug-resistant pathogenic fungi use several families of membrane-embedded transporters to efflux antifungal drugs from the cells. The efflux pump Cdr1 (Candida drug resistance 1) belongs to the ATP-binding cassette (ABC) superfamily of transporters. Cdr1 is one of the most predominant mechanisms of multidrug resistance in azole-resistant (AR) clinical isolates of Candida albicans. Blocking drug efflux represents an attractive approach to combat the multidrug resistance of this opportunistic human pathogen. In this study, we rationally designed and synthesized transmembrane peptide mimics (TMPMs) of Cdr1 protein (Cdr1p) that correspond to each of the 12 transmembrane helices (TMHs) of the two transmembrane domains of the protein to target the primary structure of the Cdr1p. Several FITC-tagged TMPMs specifically bound to Cdr1p and blocked the efflux of entrapped fluorescent dyes from the AR (Gu5) isolate. These TMPMs did not affect the efflux of entrapped fluorescent dye from cells expressing the Cdr1p homologue Cdr2p or from cells expressing a non-ABC transporter Mdr1p. Notably, the time correlation of single photon counting fluorescence measurements confirmed the specific interaction of FITC-tagged TMPMs with their respective TMH. By using mutant variants of Cdr1p, we show that these TMPM antagonists contain the structural information necessary to target their respective TMHs of Cdr1p and specific binding sites that mediate the interactions between the mimics and its respective helix. Additionally, TMPMs that were devoid of any demonstrable hemolytic, cytotoxic, and antifungal activities chemosensitize AR clinical isolates and demonstrate synergy with drugs that further improved the therapeutic potential of fluconazole in vivo.

A key structural domain of the Candida albicans Mdr1 protein.

A major multidrug transporter, MDR1 (multidrug resistance 1), a member of the MFS (major facilitator superfamily), invariably contributes to an increased efflux of commonly used azoles and thus corroborates their direct involvement in MDR in Candida albicans. The Mdr1 protein has two transmembrane domains, each comprising six transmembrane helices, interconnected with extracellular loops and ICLs (intracellular loops). The introduction of deletions and insertions through mutagenesis was used to address the role of the largest interdomain ICL3 of the MDR1 protein. Most of the progressive deletants, when overexpressed, eliminated the drug resistance. Notably, restoration of the length of the ICL3 by insertional mutagenesis did not restore the functionality of the protein. Interestingly, most of the insertion and deletion variants of ICL3 became amenable to trypsinization, yielding peptide fragments. The homology model of the Mdr1 protein showed that the molecular surface-charge distribution was perturbed in most of the ICL3 mutant variants. Taken together, these results provide the first evidence that the CCL (central cytoplasmic loop) of the fungal MFS transporter of the DHA1 (drug/proton antiporter) family is critical for the function of MDR. Unlike other homologous proteins, ICL3 has no apparent role in imparting substrate specificity or in the recruitment of the transporter protein.

RNA-binding domain of SARS-CoV2 nucleocapsid: MD simulation study of the effect of the proline substitutions P67S and P80R on the structure of the protein.

The nucleocapsid component of SARS-CoV2 is involved in the viral genome packaging. GammaP.1(Brazil) and the 20 C-US(USA) variants had a high frequency of the P80R and P67S mutations respectively in the RNA-binding domain of the nucleocapsid. Since RNA-binding domain participates in the electrostatic interactions with the viral genome, the study of the effects of proline substitutions on the flexibility of the protein will be meaningful. It evinced that the trajectory of the wildtype and mutants was stable during the simulation and exhibited distinct changes in the flexibility of the protein. Moreover, the beta-hairpin loop region of the protein structures exhibited high amplitude fluctuations and dominant motions. Additionally, modulations were detected in the drug binding site. Besides, the extent of correlation and anti-correlation motions involving the protruding region, helix, and the other RNA binding sites differed between the wildtype and mutants. The secondary structure analysis disclosed the variation in the occurrence pattern of the secondary structure elements between the proteins. Protein-ssRNA interaction analysis was also done to detect the amino acid contacts with ssRNA. R44, R59, and Y61 residues of the wildtype and P80R mutant exhibited different duration contacts with the ssRNA. It was also noticed that R44, R59, and Y61 of the wildtype and P80R formed hydrogen bonds with the ssRNA. However in P67S, residues T43, R44, R45, R40, R59, and R41 displayed contacts and formed hydrogen bonds with ssRNA. Binding free energy was also calculated and was lowest for P67S than wildtype andP80R. Thus, proline substitutions influence the structure of the RNA-binding domain and may modulate viral genome packaging besides the host-immune response.Communicated by Ramaswamy H. Sarma.

Mannose 2, 3, 4, 5, 6-O-pentasulfate (MPS): a partial activator of human heparin cofactor II with anticoagulation potential.

Thromboembolic diseases are a major cause of mortality in human and the currently available anticoagulants are associated with various drawbacks, therefore the search for anticoagulants that have better safety profile is highly desirable. Compounds that are part of the dietary routine can be modified to possibly increase their anticoagulant potential. We show mannose 2,3,4,5,6-O-pentasulfate (MPS) as a synthetically modified form of mannose that has appreciable anticoagulation properties. An in silico study identified that mannose in sulfated form can bind effectively to the heparin-binding site of antithrombin (ATIII) and heparin cofactor II (HCII). Mannose was sulfated using a simple sulfation strategy-involving triethylamine-sulfur trioxide adduct. HCII and ATIII were purified from human plasma and the binding analysis using fluorometer and isothermal calorimetry showed that MPS binds at a unique site. A thrombin inhibition analysis using the chromogenic substrate showed that MPS partially enhances the activity of HCII. Further an assessment of in vitro blood coagulation assays using human plasma showed that the activated partial thromboplastin time (APTT) and prothrombin time (PT) were prolonged in the presence of MPS. A molecular dynamics simulation analysis of the HCII-MPS complex showed fluctuations in a N-terminal loop and the cofactor binding site of HCII. The results indicate that MPS is a promising lead due to its effect on the in vitro coagulation rate.Communicated by Ramaswamy H. Sarma.

Mapping the FtsQBL divisome components in bacterial NTD pathogens as potential drug targets.

Cytokinesis is an essential process in bacterial cell division, and it involves more than 25 essential/non-essential cell division proteins that form a protein complex known as a divisome. Central to the divisome are the proteins FtsB and FtsL binding to FtsQ to form a complex FtsQBL, which helps link the early proteins with late proteins. The FtsQBL complex is highly conserved as a component across bacteria. Pathogens like Vibrio cholerae, Mycobacterium ulcerans, Mycobacterium leprae, and Chlamydia trachomatis are the causative agents of the bacterial Neglected Tropical Diseases Cholera, Buruli ulcer, Leprosy, and Trachoma, respectively, some of which seemingly lack known homologs for some of the FtsQBL complex proteins. In the absence of experimental characterization, either due to insufficient resources or the massive increase in novel sequences generated from genomics, functional annotation is traditionally inferred by sequence similarity to a known homolog. With the advent of accurate protein structure prediction methods, features both at the fold level and at the protein interaction level can be used to identify orthologs that cannot be unambiguously identified using sequence similarity methods. Using the FtsQBL complex proteins as a case study, we report potential remote homologs using Profile Hidden Markov models and structures predicted using AlphaFold. Predicted ortholog structures show conformational similarity with corresponding E. coli proteins irrespective of their level of sequence similarity. Alphafold multimer was used to characterize remote homologs as FtsB or FtsL, when they were not sufficiently distinguishable at both the sequence or structure level, as their interactions with FtsQ and FtsW play a crucial role in their function. The structures were then analyzed to identify functionally critical regions of the proteins consistent with their homologs and delineate regions potentially useful for inhibitor discovery.

Bioinformatic Identification of ABC Transporters in Candida auris.

Antifungal resistance mediated by overexpression of ABC transporters is one of the primary roadblocks to effective therapy against Candida infections. Thus, identification and characterization of the ABC transporter repertoire in Candida species are of high relevance. The method described in the chapter is based on our previously developed bioinformatic pipeline for identification of ABC proteins in Candida species. The methodology essentially involves the utilization of a hidden Markov model (HMM) profile of the nucleotide-binding domain (NBD) of ABC proteins to mine these proteins from the proteome of Candida species. Further, a widely used tool to predict membrane protein topology is exploited to identify the true transporter candidates out of the ABC proteins. Even though the chapter specifically focuses on a method to identify ABC transporters in Candida auris , the same can also be applied to any other Candida species.