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.

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.

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.

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.

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.

Identifying the Novel Inhibitors Against the Mycolic Acid Biosynthesis Pathway Target "mtFabH" of Mycobacterium tuberculosis.

Mycolic acids are the key constituents of mycobacterial cell wall, which protect the bacteria from antibiotic susceptibility, helping to subvert and escape from the host immune system. Thus, the enzymes involved in regulating and biosynthesis of mycolic acids can be explored as potential drug targets to kill Mycobacterium tuberculosis (Mtb). Herein, Kyoto Encyclopedia of Genes and Genomes is used to understand the fatty acid metabolism signaling pathway and integrative computational approach to identify the novel lead molecules against the mtFabH (ß-ketoacyl-acyl carrier protein synthase III), the key regulatory enzyme of the mycolic acid pathway. The structure-based virtual screening of antimycobacterial compounds from ChEMBL library against mtFabH results in the selection of 10 lead molecules. Molecular binding and drug-likeness properties of lead molecules compared with mtFabH inhibitor suggest that only two compounds, ChEMBL414848 (C1) and ChEMBL363794 (C2), may be explored as potential lead molecules. However, the spatial stability and binding free energy estimation of thiolactomycin (TLM) and compounds C1 and C2 with mtFabH using molecular dynamics simulation, followed by molecular mechanics Poisson-Boltzmann surface area (MM/PBSA) indicate the better activity of C2 (ΔG = -14.18 kcal/mol) as compared with TLM (ΔG = -9.21 kcal/mol) and C1 (ΔG = -13.50 kcal/mol). Thus, compound C1 may be explored as promising drug candidate for the structure-based drug designing of mtFabH inhibitors in the therapy of Mtb.

Computational Insights of Unfolding of N-Terminal Domain of TDP-43 Reveal the Conformational Heterogeneity in the Unfolding Pathway.

TDP-43 proteinopathies is a disease hallmark that characterizes amyotrophic lateral sclerosis (ALS) and frontotemporal lobar degeneration (FTLD). The N-terminal domain of TDP-43 (NTD) is important to both TDP-43 physiology and TDP-43 proteinopathy. However, its folding and dimerization process is still poorly characterized. In the present study, we have investigated the folding/unfolding of NTD employing all-atom molecular dynamics (MD) simulations in 8 M dimethylsulfoxide (DMSO) at high temperatures. The MD results showed that the unfolding of the NTD at high temperature evolves through the formation of a number of conformational states differing in their stability and free energy. The presence of structurally heterogeneous population of intermediate ensembles was further characterized by the different extents of solvent exposure of Trp80 during unfolding. We suggest that these non-natives unfolded intermediate ensembles may facilitate NTD oligomerization and subsequently TDP-43 oligomerization, which might lead to the formation of irreversible pathological aggregates, characteristics of disease pathogenesis.

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.

ICMR's Antimicrobial Resistance Surveillance system (i-AMRSS): a promising tool for global antimicrobial resistance surveillance.

BACKGROUND: Growing resistance to antimicrobials has become an important health issue of the 21st century. Many international, national and local approaches are being employed for the control and prevention of antimicrobial resistance (AMR). Among them, surveillance is reported to be the best method to reduce the spread of infection and thereby AMR. An integral component of AMR surveillance is the informatics suite for collection, storage and analysis of surveillance data. METHODS: Considering the traits of an optimal surveillance tool and constraints with existing tools, Indian Council of Medical Research (ICMR) initiated the design and development of ICMR's Antimicrobial Resistance Surveillance system (i-AMRSS). i-AMRSS is a web-based tool built using modular architecture. It is capable of collecting standardized data from small laboratories to generate local and nationwide reports. RESULTS: i-AMRSS is a robust, comprehensive, modular, extensible and intelligent open-source tool piloted in ICMR's AMR Network (31 hospitals and laboratories across India) since 2016. The developed tool has collected more than 280 000 patient records to date. CONCLUSIONS: The standardized data collected through i-AMRSS would be valuable for various collaborators to monitor outbreaks and infection control practices, evaluate transmission dynamics and formulate antibiotic use and selling policies. The tool is presently being used to capture human testing and consumption data, however, it can be extended for AMR surveillance using a 'One Health' approach.

ABC-finder: A containerized web server for the identification and topology prediction of ABC proteins.

In view of the multiple clinical and physiological implications of ABC transporter proteins, there is a considerable interest among researchers to characterize them functionally. However, such characterizations are based on the premise that ABC proteins are accurately identified in the proteome of an organism, and their topology is correctly predicted. With this objective, we have developed ABC-finder, i.e., a Docker-based package for the identification of ABC proteins in all organisms, and visualization of the topology of ABC proteins using a web browser. ABC-finder is built and deployed in a Linux container, making it scalable for many concurrent users on our servers and enabling users to download and run it locally. Overall, ABC-finder is a convenient, portable, and platform-independent tool for the identification and topology prediction of ABC proteins. ABC-finder is accessible at http://abc-finder.osdd.jnu.ac.in.

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.

Structural heterogeneity in RNA recognition motif 2 (RRM2) of TAR DNA-binding protein 43 (TDP-43): clue to amyotrophic lateral sclerosis.

Aberrant misfolding and aggregation of TAR DNA-binding protein 43 (TDP-43) and its fragments have been implicated in amyotrophic lateral sclerosis (ALS) and other neurodegenerative diseases. Within the protein, the second RNA recognition motif (RRM2) has recently been demonstrated to be a major contributor towards aggregation and the resultant toxicity. However, the physicochemical mechanism of its misfolding from the functional folded state is poorly understood. In the present work, we have used a cumulative ∼2µs of molecular dynamics (MD) simulation to study the structural and thermodynamic characteristics of different unfolded intermediates of RRM2 domain of TDP-43. In 6 M GdmCl at 400 K, at RMSD around 1.5 nm, part of the secondary structure i.e. helix still does not melt without significant change in solvent accessibility and intra-protein hydrogen bonds. However, hydrophobic contacts disrupt significantly suggesting that unfolding proceeds through disruption of hydrophobic core of the protein.The temperature dependent free-energy landscapes (FELs) reveal the presence of multiple metastable intermediate states stabilized by hydrophobic (ILV) contacts and hydrogen bonds. These conformational states have all the native helices intact with significant loss of ß-sheets. These partially unfolded states are quite compact and characterized by the exposure of aggregation-prone ß-sheets, suggesting the increased aggregation propensity of the partially unfolded states. Our results will thus serve to uncover the structural properties of partially unfolded intermediate states that drive TDP-43 misfolding and aggregation. Elucidating the structural characterization of the misfolding and aggregation prone intermediate states of TDP-43 are important to understand its role in ALS and other neurodegenerative diseases.Communicated by Ramaswamy H. Sarma.

Virtual screening and free energy estimation for identifying Mycobacterium tuberculosis flavoenzyme DprE1 inhibitors.

In Mycobacterium tuberculosis (MTB), the cell wall synthesis flavoenzyme decaprenylphosphoryl-ß-d-ribose 2'-epimerase (DprE1) plays a crucial role in host pathogenesis, virulence, lethality and survival under stress. The emergence of different variants of drug resistant MTB are a major threat worldwide which essentially requires more effective new drug molecules with no major side effects. Here, we used structure based virtual screening of bioactive molecules from the ChEMBL database targeting DprE1, having bioactive 78,713 molecules known for anti-tuberculosis activity. An extensive molecular docking, binding affinity and pharmacokinetics profile filtering results in the selection four compounds, C5 (ChEMBL2441313), C6 (ChEMBL2338605), C8 (ChEMBL441373) and C10 (ChEMBL1607606) which may explore as potential drug candidates. The obtained results were validated with thirteen known DprE1 inhibitors. We further estimated the free-binding energy, solvation and entropy terms underlying the binding properties of DprE1-ligand interactions with the implication of MD simulation, MM/GBSA, MM/PBSA and MM/3D-RISM. Interestingly, we find that C6 shows the highest ΔG scores (-41.28 ± 3.51, -22.36 ± 3.17, -10.33 ± 5.70 kcal mol-1) in MM/GBSA, MM/PBSA and MM/3D-RISM assay, respectively. Whereas, the lowest ΔG scores (-35.31 ± 3.44, -13.67 ± 2.65, -3.40 ± 4.06 kcal mol-1) observed for CT319, the inhibitor co-crystallized with DprE1. Collectively, the results demonstrated that hit-molecules: C5, C6, C8 and C10 having better binding free energy and molecular affinity as compared to CT319. Thus, we proposed that selected compounds may be explored as lead molecules in MTB therapy.

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.

Effects of natural mutations (L94I and L94V) on the stability and mechanism of folding of horse cytochrome c: A combined in vitro and molecular dynamics simulations approach.

Known crystal structures of 10 cytochromes (cyts) c from different sources led to the conclusion that natural mutations in these proteins does not affect their 3D structure, hence evolution preserved structure for function. A sequence alignment of horse cyt c with all other 284 cyts c led to two important conclusions: (i) Leu at position 94 is conserved in all 30 mammalian known sequences, and (ii) there are 14 other species which have either Val or Ile at 94th position. We asked a question: Is the avoidance of substitution by Val or Ile at position 94 in the mammalian cyts c by design or by chance? To answer this question, we introduced natural substitutes of Leu94 by Val and Ile in horse cyt c using site-directed mutagenesis. Here, from our in vitro and molecular dynamic simulation studies on L94V and L94I mutants, we concluded that (i) although the natural mutations destabilize the wild type cyt c, it does not significantly affect the mechanism of folding of the protein, (ii) urea-induced denaturation of WT cyt c and its mutants is a two-state process, and (iii) denaturation of WT cyt c and its mutants by guanidinium chloride is not a two-state process.

Development of novel N-(6-methanesulfonyl-benzothiazol-2-yl)-3-(4-substituted-piperazin-1-yl)-propionamides with cholinesterase inhibition, anti-ß-amyloid aggregation, neuroprotection and cognition enhancing properties for the therapy of Alzheimer's disease.

A novel series of benzothiazole-piperazine hybrids were rationally designed, synthesized, and evaluated as multifunctional ligands against Alzheimer's disease (AD). The synthesized hybrid molecules illustrated modest to strong inhibition of acetylcholinesterase (AChE) and Aß1-42 aggregation. Compound 12 emerged as the most potent hybrid molecule exhibiting balanced functions with effective, uncompetitive and selective inhibition against AChE (IC50 = 2.31 µM), good copper chelation, Aß1-42 aggregation inhibition (53.30%) and disaggregation activities. Confocal laser scanning microscopy and TEM analysis also validate the Aß fibril inhibition ability of this compound. Furthermore, this compound has also shown low toxicity and is capable of impeding loss of cell viability elicited by H2O2 neurotoxicity in SHSY-5Y cells. Notably, compound 12 significantly improved cognition and spatial memory against scopolamine-induced memory deficit in a mouse model. Hence, our results corroborate the multifunctional nature of novel hybrid molecule 12 against AD and it may be a suitable lead for further development as an effective therapeutic agent for therapy in the future.

Cytochrome P450 2C9 polymorphism: Effect of amino acid substitutions on protein flexibility in the presence of tamoxifen.

Tamoxifen is a prodrug and cytochrome P450 2C9 (CYP2C9) has a significant role in the formation of a therapeutically more potent metabolite (4-hydroxytamoxifen) than tamoxifen. Since CYP2C9 exhibits genetic polymorphism, it may contribute to different phenotypic drug response. Moreover, it may be misleading if the possibility of heterogeneous clinical observations of pharmacogenetic investigations is ignored. Above all, clinical investigation of all the polymorphic variants is beyond the scope of a pharmacogenetic study. Therefore, in order to understand the genotype-phenotype association, it is aimed to study the interatomic interactions of amino acid substitutions in CYP2C9 variants in the presence of tamoxifen. Computational structural biology approach was adopted to study the effect of amino acid substitutions of polymorphic variants of CYP2C9 R144C (*2), I359 L (*3), D360E (*5), R150H (*8), R335W (*11) and L90 P (*13) on the flexibility of the enzyme in the presence of tamoxifen. The mutations were selected based on previously determined associations on genotype and clinical outcome of drugs. Against the above plane, docking of tamoxifen was performed with the crystal structure representing the wild-type form of the enzyme. The docked conformation of tamoxifen was favourable for 4-hydroxylation with the site of metabolism within 5 Šof oxyferrylheme consistent with the drug metabolism pathway of tamoxifen. Further, the effect of amino acid substitutions CYP2C9 variants on the protein flexibility in the presence of tamoxifen in 4-hydroxy orientation was evaluated by molecular dynamics (MD) simulations. Distinct protein flexibility modulations between variants were observed in F/G segment constituting the substrate access/egress channels, helix B' involved with substrate specificity and helix I associated with the holding of substrates. Root Mean Square Fluctuation analysis of the trajectories of variants exhibited fluctuations in F/G segment, B' and I helix. Dominant motions in the structure were identified by performing Principal Component Analysis on trajectories and the porcupine plot depicted displaced F/G segment in variants. Thus, the interatomic interaction study of CYP2C9 variants in the presence of tamoxifen predicts the plausible effect of the investigated variants on the therapeutic outcome of tamoxifen. It is presumed that the observations of the study would be meaningful to understand tamoxifen pharmacogenetics.

Delineating the conformational dynamics of intermediate structures on the unfolding pathway of ß-lactoglobulin in aqueous urea and dimethyl sulfoxide.

The funnel shaped energy landscape model of the protein folding suggests that progression of folding proceeds through multiple pathways, having the multiple intermediates which leads to multidimensional free-energy surface. Herein, we applied all-atom MD simulation to conduct a comparative study on the structure of ß-lactoglobulin (ß-LgA) in aqueous mixture of 8 M urea and 8 M dimethyl sulfoxide (DMSO), at different temperatures. The cumulative results of multiple simulations suggest a common unfolding pathway of ß-LgA, occurred through the stable and meta-stable intermediates (I), in both urea and DMSO. However, the free-energy landscape (FEL) analyses show that the structural transitions of I-states are energetically different. In urea, FEL shows distinct ensemble of intermediates, I1 and I2, separated by the energy barrier of ∼3.0 kcal mol-1. Similarly, we find the population of two distinct I1 and I2 states in DMSO, however, the I1 appeared transiently around ∼30-35 ns and is short-lived. But, the I2 ensemble is observed structurally compact and long-lived (∼50-150 ns) as compared to unfolding in urea. Furthermore, the I1 and I2 are separated through a high energy barrier of ∼6.0 kcal mol-1. Thus, our results provide the structural insights of intermediates which essentially bear the signature of a different unfolding pathway of ß-LgA in urea and DMSO.Abbreviationsß-LgAß-lactoglobulinDMSOdimethyl sulfoxideFELfree-energy landscapeGdmClguanidinium chlorideIintermediate stateMGmolten globule statePMEparticle mesh EwaldQfraction of native contactsRMSDroot mean square deviationRMSFroot mean square fluctuationRgradius of gyrationSASAsolvent Accessible Surface AreascSASAthe side chain SASATrptryptophanCommunicated by Ramaswamy H. Sarma.