Structural basis for drug resistance mechanisms against anaplastic lymphoma kinase.

Drug resistance to anaplastic lymphoma kinase (ALK) inhibitors (crizotinib and ceritinib) is caused by mutation in the region encoding kinase domain of ALK. Compounds with potential ability to inhibit all strains of ALK are a solution to tackle the problem of drug resistance. In this study, we delineated positions of residues possessing the ability to make ALK drug resistant upon mutation by assessing them using five parameters (conservation index, binding-site root-mean-square deviation, protein structure stability, change in ATP, and drug-binding affinity). Four residual positions (Leu 1122, Thr 1151, Phe 1245, and Gly 1269) were ascertained. This study will be beneficial for designing drugs with better proficiency against ALK and the issues of drug resistance. This study can be taken as a pipeline for investigating drug-resistant mutations in other diseases as well.

Computational Screening and Exploration of Disease-Associated Genes in Alzheimer's Disease.

Alzheimer's is a neurodegenerative disease affecting large populations worldwide characterized mainly by progressive loss of memory along with various other symptoms. The foremost cause of the disease is still unclear, however various mechanisms have been proposed to cause the disease that include amyloid hypothesis, tau hypothesis, and cholinergic hypothesis in addition to genetic factors. Various genes have been known to be involved which are APOE, PSEN1, PSEN2, and APP among others. In the present study, we have used computational methods to examine the pathogenic effects of non-synonymous single nucleotide polymorphisms (SNPs) associated with ABCA7, CR1, MS4A6A, CD2AP, PSEN1, PSEN2, and APP genes. The SNPs were obtained from dbSNP database followed by identification of deleterious SNPs and prediction of their functional impact. Prediction of disease-associated mutations was performed and the impact of the mutations on the stability of the protein was carried out. To study the structural significance of the computationally prioritized mutations on the proteins, molecular dynamics simulation studies were carried out. On analysis, the SNPs with IDs rs76282929 ABCA7; CR1 rs55962594; MS4A6A rs601172; CD2AP rs61747098; PSEN1 rs63750231, rs63750265, rs63750526, rs63750577, rs63750687, rs63750815, rs63750900, rs63751037, rs63751163, rs63751399; PSEN2 rs63749851; and APP rs63749964, rs63750066, rs63750734, and rs63751039 were predicted to be deleterious and disease-associated having significant structural impact on the proteins. The current study proposes a precise computational methodology for the identification of disease-associated SNPs. J. Cell. Biochem. 118: 1471-1479, 2017. © 2016 Wiley Periodicals, Inc.

Double Mutants in DNA Gyrase Lead to Ofloxacin Resistance in Mycobacterium tuberculosis.

Fluoroquinolones are among the most important classes of highly effective antibacterial drugs, exhibiting wide range of activity to cure infectious diseases. Ofloxacin is second generation fluoroquinolone approved by FDA for the treatment of tuberculosis by selectively inhibiting DNA gyrase. However, the emergence of drug resistance owing to mutations in DNA gyrase poses intimidating challenge for the effective therapy of this drug. The double mutants GyrAA90V GyrBD500N and GyrAA90V GyrBT539N are reported to be implicated in conferring higher levels of OFX resistance. The present study was designed to unravel the molecular principles behind development of resistance by the bug against fluoroquinolones. Our results highlighted that polar interactions play critical role in the development of drug resistance and highlight the significant correlation between the free energy calculations predicted by MM-PBSA and stability of the ligand-bound complexes. Modifications at the OFX binding pocket due to amino acid substitution leads to fewer hydrogen bonds in mutants DNA gyrase-OFX complex, which determined the low susceptibility of the ligand in inhibiting the mutant protein. This study provides a structural rationale to the mutation-based resistance to ofloxacin and will pave way for development potent fluoroquinolone-based resistant-defiant drugs. J. Cell. Biochem. 118: 2950-2957, 2017. © 2017 Wiley Periodicals, Inc.

Natural polyphenolic inhibitors against the antiapoptotic BCL-2.

The apoptotic mechanism is regulated by the BCL-2 family of proteins, such as BCL-2 or Bcl-xL, which block apoptosis while Bad, Bak, Bax, Bid, Bim or Hrk induce apoptosis. The overexpression of BCL-2 was found to be related to the progression of cancer and also providing resistance towards chemotherapeutic treatments. In the present study, we found that all polyphenols (apigenin, fisetin, galangin and luteolin) bind to the hydrophobic groove of BCL-2 and the interaction is stable throughout MD simulation run. Luteolin was found to bind with highest negative binding energy and thus, claimed highest potency towards BCL-2 inhibition followed by fisetin. The hydrophobic interactions were found to be critical for stable complex formation as revealed by the vdW energy and ligplot analysis. Finally, on the basis of data obtained during the study, it can be concluded that these polyphenols have the potential to be used as lead molecules for BCL-2 inhibition.

Molecular dynamics-based identification of novel natural mortalin-p53 abrogators as anticancer agents.

INTRODUCTION: Cancer is one of the leading causes of mortality worldwide that requires attention in terms of extensive study and research. Eradication of mortalin-p53 interaction that leads to the inhibition of transcriptional activation or blocking of p53 from functioning as a suppressor and induction of nuclear translocation of p53 can prove to be one of the useful approaches for cancer management. RESULTS: In this study, we used structure-based approach to target the p53-binding domain of mortalin in order to prevent mortalin-p53 complex formation. We screened compounds from ZINC database against the modeled mortalin protein using Glide virtual screening. The top two compounds, DTOM (ZINC 28639308) and TTOM (ZINC 38143676) with Glide score of -12.27 and -12.16, respectively, were identified with the potential to abrogate mortalin-p53 interaction. Finally, molecular dynamics simulations were used to analyze the dynamic stability of the ligand-bound complex and it was observed that residues Tyr196, Asn198, Val264 and Thr267 were involved in intermolecular interactions in both the simulated ligand-bound complexes, and thus, these residues may have a paramount role in stabilizing the binding of the ligands with the protein. CONCLUSION: These detailed insights can further facilitate the development of potent inhibitors against mortalin-p53 complex.

Novel group-based QSAR and combinatorial design of CK-1δ inhibitors as neuroprotective agents.

BACKGROUND: Tar DNA binding protein 43 (TDP-43) hyperphosphorylation, caused by Casein kinase 1 (CK-1) protein isoforms, is associated with the onset and progression of Amyotrophic Lateral Sclerosis (ALS). Among the reported isoforms and splice variants of CK-1 protein superfamily, CK-1δ is known to phosphorylate different serine and threonine sites on TDP-43 protein in vitro and thus qualifies as a potential target for ALS treatment. RESULTS: The developed GQSAR (group based quantitative structure activity relationship) model displayed satisfactory statistical parameters for the dataset of experimentally reported N-Benzothiazolyl-2-Phenyl Acetamide derivatives. A combinatorial library of molecules was also generated and the activities were predicted using the statistically sound GQSAR model. Compounds with higher predicted inhibitory activity were screened against CK-1δ that resulted in to the potential novel leads for CK-1δ inhibition. CONCLUSIONS: In this study, a robust fragment based QSAR model was developed on a congeneric set of experimentally reported molecules and using combinatorial library approach, a series of molecules were generated from which we report two top scoring, CK-1δ inhibitors i.e., CHC (6-benzyl-2-cyclopropyl-4-{[(4-cyclopropyl-6-ethyl-1,3-benzothiazol-2-yl)carbamoyl]methyl}j-3-fluorophenyl hydrogen carbonate) and DHC (6-benzyl-4-{[(4-cyclopropyl-6-ethyl-1,3-benzothiazol-2-yl)carbamoyl]methyl}-2-(decahydronaphthalen-1-yl)-3-hydroxyphenyl hydrogen carbonate) with binding energy of -6.11 and -6.01 kcal/mol, respectively.

Molecular modeling and lead design of substituted zanamivir derivatives as potent anti-influenza drugs.

BACKGROUND: Influenza virus spreads infection by two main surface glycoproteins, namely hemagglutinin (HA) and neuraminidase (NA). NA cleaves the sialic acid receptors eventually releasing newly formed virus particles which then invade new cells. Inhibition of NA could limit the replication of virus to one round which is insufficient to cause the disease. RESULTS: An experimentally reported series of acylguanidine zanamivir derivatives was used to develop GQSAR model targeting NA in different strains of influenza virus, H1N1 and H3N2. A combinatorial library was developed and their inhibitory activities were predicted using the GQSAR model. CONCLUSION: The top leads were analyzed by docking which revealed the binding modes of these inhibitors in the active site of NA (150-loop). The top compound (AMA) was selected for carrying out molecular dynamics simulations for 15 ns which provided insights into the time dependent dynamics of the designed leads. AMA possessed a docking score of -8.26 Kcal/mol with H1N1 strain and -7.00 Kcal/mol with H3N2 strain. Ligand-bound complexes of both H1N1 and H3N2 were observed to be stable for 11 ns and 7 ns respectively. ADME descriptors were also calculated to study the pharmacokinetic properties of AMA which revealed its drug-like properties.

Integrating network, sequence and functional features using machine learning approaches towards identification of novel Alzheimer genes.

BACKGROUND: Alzheimer's disease (AD) is a complex progressive neurodegenerative disorder commonly characterized by short term memory loss. Presently no effective therapeutic treatments exist that can completely cure this disease. The cause of Alzheimer's is still unclear, however one of the other major factors involved in AD pathogenesis are the genetic factors and around 70 % risk of the disease is assumed to be due to the large number of genes involved. Although genetic association studies have revealed a number of potential AD susceptibility genes, there still exists a need for identification of unidentified AD-associated genes and therapeutic targets to have better understanding of the disease-causing mechanisms of Alzheimer's towards development of effective AD therapeutics. RESULTS: In the present study, we have used machine learning approach to identify candidate AD associated genes by integrating topological properties of the genes from the protein-protein interaction networks, sequence features and functional annotations. We also used molecular docking approach and screened already known anti-Alzheimer drugs against the novel predicted probable targets of AD and observed that an investigational drug, AL-108, had high affinity for majority of the possible therapeutic targets. Furthermore, we performed molecular dynamics simulations and MM/GBSA calculations on the docked complexes to validate our preliminary findings. CONCLUSIONS: To the best of our knowledge, this is the first comprehensive study of its kind for identification of putative Alzheimer-associated genes using machine learning approaches and we propose that such computational studies can improve our understanding on the core etiology of AD which could lead to the development of effective anti-Alzheimer drugs.

Structural studies on molecular mechanisms of Nelfinavir resistance caused by non-active site mutation V77I in HIV-1 protease.

BACKGROUND: The human immunodeficiency virus (HIV-1) is a retrovirus causing acquired immunodeficiency syndrome (AIDS), which has become a serious problem across the world and has no cure reported to date. Human immunodeficiency virus (HIV-1) protease is an attractive target for antiviral treatment and a number of therapeutically useful inhibitors have been designed against it. The emergence of drug resistant mutants of HIV-1 poses a serious problem for conventional therapies that have been used so far. Until now, thirteen protease inhibitors (PIs), major mutation sites and many secondary mutations have been listed in the HIV Drug Resistance Database. In this study, we have studied the effect of the V77I mutation in HIV-PR along with the co-occurring mutations L33F and K20T through multi-nanosecond molecular dynamics simulations. V77I is known to cause Nelfinavir (NFV) resistance in the subtype B population of HIV-1 protease. We have for the first time reported the effect of this clinically relevant mutation on the binding of Nelfinavir and the conformational flexibility of the protease. RESULTS: Two HIV-PR mutants have been considered in this study - the Double Mutant Protease (DBM) V77I-L33F and Triple Mutant Protease (TPM) V77I-K20T-L33F. The molecular dynamics simulation studies were carried out and the RMSD trajectories of the unliganded wild type and mutated protease were found to be stable. The binding affinity of NFV with wild type HIV-PR was very high with a Glide XP docking score of -9.3 Kcal/mol. NFV showed decreased affinity towards DBM with a docking score of -8.0 Kcal/mol, whereas its affinity increased towards TPM (Glide XP score: -10.3). Prime/MM-GBSA binding free energy of the wild type, DBM and TPM HIV-PR docked structures were calculated as -38.9, -11.1 and -42.6 Kcal/mol respectively. The binding site cavity volumes of wild type, DBM and TPM protease were 1186.1, 1375.5 and 1042.5 Å3 respectively. CONCLUSION: In this study, we have studied the structural roles of the two HIV-PR mutations by conducting molecular dynamics simulation studies of the wild type and mutant HIV-1 PRs. The present study proposes that DBM protease showed greater flexibility and the flap separation was greater with respect to the wild type protease. The cavity size of the MD-stabilized DBM was also found to be increased, which may be responsible for the decreased interaction of Nelfinavir with the cavity residues, thus explaining the decreased binding affinity. On the other hand, the binding affinity of NFV for TPM was found to be enhanced, accounted for by the decrease in cavity size of the mutant which facilitated strong interactions with the flap residues. The flap separation of TPM was less than the wild type protease and the decreased cavity size may be responsible for its lower resistance, and hence, may be the reason for its lower clinical relevance.

Structural investigations of T854A mutation in EGFR and identification of novel inhibitors using structure activity relationships.

BACKGROUND: The epidermal growth factor receptor (EGFR) is a member of the ErbB family that is involved in a number of processes responsible for cancer development and progression such as angiogenesis, apoptosis, cell proliferation and metastatic spread. Malfunction in activation of protein tyrosine kinases has been shown to result in uncontrolled cell growth. The EGFR TK domain has been identified as suitable target in cancer therapy and tyrosine kinase inhibitors such as erlotinib have been used for treatment of cancer. Mutations in the region of the EGFR gene encoding the tyrosine kinase (TK) domain causes altered responses to EGFR TK inhibitors (TKI). In this paper we perform molecular dynamics simulations and PCA analysis on wild-type and mutant (T854A) structures to gain insight into the structural changes observed in the target protein upon mutation. We also report two novel inhibitors identified by combined approach of QSAR model development. RESULTS: The wild-type and mutant structure was observed to be stable for 26 ns and 24 ns respectively. In PCA analysis, the mutant structure proved to be more flexible than wild-type. We developed a 3D-QSAR model using 38 thiazolyl-pyrazoline compounds which was later used for prediction of inhibitory activity of natural compounds of ZINC library. The 3D-QSAR model was proved to be robust by the statistical parameters such as r2 (0.9751), q2(0.9491) and pred_r2(0.9525). CONCLUSION: Analysis of molecular dynamics simulations results indicate stability loss and increased flexibility in the mutant structure. This flexibility results in structural changes which render the mutant protein drug resistant against erlotinib. We report two novel compounds having high predicted inhibitory activity to EGFR TK domain with both wild-type and mutant structure.

Abrogation of AuroraA-TPX2 by novel natural inhibitors: molecular dynamics-based mechanistic analysis.

INTRODUCTION: Cancer is characterized by uncontrolled cell growth and genetic instabilities. The human Aurora-A kinase protein plays a crucial role in spindle assembly during mitosis and is activated by another candidate oncogene, targeting protein for Xklp2 (TPX2). It has been proposed that dissociation of Aurora A-TPX2 complex leads to disruption of mitotic spindle apparatus, thereby preventing cell division and further tumor growth. MATERIALS AND METHODS: A large natural compound library was docked against the active site of Aurora A-TPX2 complex. The protein-ligand complexes were subjected to molecular dynamics simulation to ascertain their binding stability. The drug properties of the compounds were analyzed to observe their drug-like properties. RESULTS: The virtual screening of natural compound library yielded two high scoring compounds, the first compound CTOM [ZINC ID: 38143674] (Glide score: -9.49) was stable for 17 ns while the second TTOM (Glide score: -9.07) was stable for 15 ns. While CTOM interacted with His280, Thr288 of Aurora A and Tyr34, Lys38 of TPX2, TTOM interacted with Arg285 and Arg286 in addition to the residues involved with CTOM. CONCLUSIONS: We report two natural compounds as potential drugs leads for the disruption of this complex. These ligands show a preferable docking score and have many drugs like properties within in the range of 95% of known drugs. The study provides evidence that CTOM and TTOM can efficiently inhibit the TPX2-mediated activation of Aurora A. Thus, it paves way for an elaborate investigation and establishes the importance of computational approaches as time- and cost-effective techniques.

Computational identification of novel natural inhibitors of glucagon receptor for checking type II diabetes mellitus.

BACKGROUND: Interaction of the small peptide hormone glucagon with glucagon receptor (GCGR) stimulates the release of glucose from the hepatic cells during fasting; hence GCGR performs a significant function in glucose homeostasis. Inhibiting the interaction between glucagon and its receptor has been reported to control hepatic glucose overproduction and thus GCGR has evolved as an attractive therapeutic target for the treatment of type II diabetes mellitus. RESULTS: In the present study, a large library of natural compounds was screened against 7 transmembrane domain of GCGR to identify novel therapeutic molecules that can inhibit the binding of glucagon with GCGR. Molecular dynamics simulations were performed to study the dynamic behaviour of the docked complexes and the molecular interactions between the screened compounds and the ligand binding residues of GCGR were analysed in detail. The top scoring compounds were also compared with already documented GCGR inhibitors- MK-0893 and LY2409021 for their binding affinity and other ADME properties. Finally, we have reported two natural drug like compounds PIB and CAA which showed good binding affinity for GCGR and are potent inhibitor of its functional activity. CONCLUSION: This study contributes evidence for application of these compounds as prospective small ligand molecules against type II diabetes. Novel natural drug like inhibitors against the 7 transmembrane domain of GCGR have been identified which showed high binding affinity and potent inhibition of GCGR.

Fragment based group QSAR and molecular dynamics mechanistic studies on arylthioindole derivatives targeting the α-ß interfacial site of human tubulin.

BACKGROUND: A number of microtubule disassembly blocking agents and inhibitors of tubulin polymerization have been elements of great interest in anti-cancer therapy, some of them even entering into the clinical trials. One such class of tubulin assembly inhibitors is of arylthioindole derivatives which results in effective microtubule disorganization responsible for cell apoptosis by interacting with the colchicine binding site of the ß-unit of tubulin close to the interface with the α unit. We modelled the human tubulin ß unit (chain D) protein and performed docking studies to elucidate the detailed binding mode of actions associated with their inhibition. The activity enhancing structural aspects were evaluated using a fragment-based Group QSAR (G-QSAR) model and was validated statistically to determine its robustness. A combinatorial library was generated keeping the arylthioindole moiety as the template and their activities were predicted. RESULTS: The G-QSAR model obtained was statistically significant with r2 value of 0.85, cross validated correlation coefficient q2 value of 0.71 and pred_r2 (r2 value for test set) value of 0.89. A high F test value of 65.76 suggests robustness of the model. Screening of the combinatorial library on the basis of predicted activity values yielded two compounds HPI (predicted pIC50 = 6.042) and MSI (predicted pIC50 = 6.001) whose interactions with the D chain of modelled human tubulin protein were evaluated in detail. A toxicity evaluation resulted in MSI being less toxic in comparison to HPI. CONCLUSIONS: The study provides an insight into the crucial structural requirements and the necessary chemical substitutions required for the arylthioindole moiety to exhibit enhanced inhibitory activity against human tubulin. The two reported compounds HPI and MSI showed promising anti cancer activities and thus can be considered as potent leads against cancer. The toxicity evaluation of these compounds suggests that MSI is a promising therapeutic candidate. This study provided another stepping stone in the direction of evaluating tubulin inhibition and microtubule disassembly degeneration as viable targets for development of novel therapeutics against cancer.

Mechanistic insights into mode of action of potent natural antagonists of BACE-1 for checking Alzheimer's plaque pathology.

Alzheimer's is a neurodegenerative disorder resulting in memory loss and decline in cognitive abilities. Accumulation of extracellular beta amyloidal plaques is one of the major pathology associated with this disease. ß-Secretase or BACE-1 performs the initial and rate limiting step of amyloidic pathway in which 37-43 amino acid long peptides are generated which aggregate to form plaques. Inhibition of this enzyme offers a viable prospect to check the growth of these plaques. Numerous efforts have been made in recent years for the generation of BACE-1 inhibitors but many of them failed during the preclinical or clinical trials due to drug related or drug induced toxicity. In the present work, we have used computational methods to screen a large dataset of natural compounds to search for small molecules having BACE-1 inhibitory activity with low toxicity to normal cells. Molecular dynamics simulations were performed to analyze molecular interactions between the screened compounds and the active residues of the enzyme. Herein, we report two natural compounds of inhibitory nature active against ß-secretase enzyme of amyloidic pathway and are potent lead molecules against Alzheimer's disease.

Mechanistic insights into mode of action of novel natural cathepsin L inhibitors.

BACKGROUND: Development of a cancerous cell takes place when it ceases to respond to growth-inhibiting signals and multiplies uncontrollably and can detach and move to other parts of the body; the process called as metastasis. A particular set of cysteine proteases are very active during cancer metastasis, Cathepsins being one of them. They are involved in tumor growth and malignancy and have also been reported to be overexpressed in tumor cell lines. In the present study, a combinatorial approach comprising three-dimensional quantitative structure-activity relationship (3D QSAR), ligand-based pharmacophore modelling and search followed by cathepsin L structure-based high throughput screening was carried out using an initial set of 28 congeneric thiosemicarbazone derivatives as cathepsin L inhibitors. A 3D QSAR was derived using the alignment of a common thiosemicarbazone substructure. Essential structural features responsible for biological activity were taken into account for development of a pharmacophore model based on 29 congeneric thiosemicarbazone derivatives. This model was used to carry out an exhaustive search on a large dataset of natural compounds. A further cathepsin L structure-based screen identified two top scoring compounds as potent anti-cancer leads. RESULTS: The generated 3D QSAR model showed statistically significant results with an r(2) value of 0.8267, cross-validated correlation coefficient q(2) of 0.7232, and a pred_r(2) (r(2) value for test set) of 0.7460. Apart from these, a high F test value of 30.2078 suggested low probability of the model's failure. The pharmacophoric hypothesis chosen for searching the natural compound libraries was identified as DDHRR, where two Ds denote 2 hydrogen donors, H represents a hydrophobic group and two Rs represent aromatic rings, all of which are essential for the biological activity. We report two potential drug leads ZINC08764437 (NFP) and ZINC03846634 (APQ) obtained after a combined approach of pharmacophore-based search and structure-based virtual screen. These two compounds displayed extra precision docking scores of -7.972908 and -7.575686 respectively suggesting considerable binding affinity for cathepsin L. High activity values of 5.72 and 5.75 predicted using the 3D QSAR model further substantiated the inhibitory potential of these identified leads. CONCLUSION: The present study attempts to correlate the structural features of thiosemicarbazone group with their biological activity by development of a robust 3D QSAR model. Being statistically valid, this model provides near accurate values of the activities predicted for the congeneric set on which it is based. These predicted activities are good for the test set compounds making it indeed a statistically sound 3D QSAR model. The identified pharmacophore model DDHRR.8 comprised of all the essential features required to interact with the catalytic triad of cathepsin L. A search for natural compounds based on this pharmacophore followed by docking studies further screened out two top scoring candidates: NFP and AFQ. The high binding affinity and presence of essential structural features in these two compounds make them ideal for consideration as natural anti-tumoral agents. Activity prediction using 3D QSAR model further validated their potential as worthy drug candidates against cathepsin L for treatment of cancer.

Novel missense mutations in gidB gene associated with streptomycin resistance in Mycobacterium tuberculosis: insights from molecular dynamics.

Streptomycin was the first antibiotic used for the treatment of tuberculosis by inhibiting translational proof reading. Point mutation in gidB gene encoding S-adenosyl methionine (SAM)-dependent 7-methylguanosine (m7G) methyltransferase required for methylation of 16S rRNA confers streptomycin resistance. As there was no structural substantiation experimentally, gidB protein model was built by threading algorithm. In this work, molecular dynamics (MD) simulations coupled with binding free energy calculations were performed to outline the mechanism underlying high-level streptomycin resistance associated with three novel missense mutants including S70R, T146M, and R187M. Results from dynamics analyses suggested that the structure distortion in the binding pocket of gidB mutants modulate SAM binding affinity. At the structural level, these conformational changes bring substantial decrease in the number of residues involved in hydrogen bonding and dramatically reduce thermodynamic stability of mutant gidB-SAM complexes. The outcome of comparative analysis of the MD simulation trajectories revealed lower conformational stability associated with higher flexibility in mutants relative to the wild-type, turns to be major factor driving the emergence of drug resistance toward antibiotic. This study will pave way toward design and development of resistant defiant gidB inhibitors as potent anti-TB agents.

Structural investigations on mechanism of lapatinib resistance caused by HER-2 mutants.

HER-2 belongs to the human epidermal growth factor receptor (HER) family. Via different signal transduction pathways, HER-2 regulates normal cell proliferation, survival, and differentiation. Recently, it was reported that MCF10A, BT474, and MDA-MB-231 cells bearing the HER2 K753E mutation were resistant to lapatinib. Present study revealed that HER-2 mutant K753E showed some contrasting behaviour as compared to wild, L768S and V773L HER-2 in complex with lapatinib while similar to previously known lapatinib resistant L755S HER-2 mutant. Lapatinib showed stable but reverse orientation in binding site of K753E and the highest binding energy among studied HER2-lapatinib complexes but slightly lesser than L755S mutant. Results indicate that K753E has similar profile as L755S mutant for lapatinib. The interacting residues were also found different from other three studied forms as revealed by free energy decomposition and ligplot analysis.

Dynamics of fluoroquinolones induced resistance in DNA gyrase of Mycobacterium tuberculosis.

DNA gyrase is a validated target of fluoroquinolones which are key components of multidrug resistance tuberculosis (TB) treatment. Most frequent occurring mutations associated with high level of resistance to fluoroquinolone in clinical isolates of TB patients are A90V, D94G, and A90V-D94G (double mutant [DM]), present in the larger subunit of DNA Gyrase. In order to explicate the molecular mechanism of drug resistance corresponding to these mutations, molecular dynamics (MD) and mechanics approach was applied. Structure-based molecular docking of complex comprised of DNA bound with Gyrase A (large subunit) and Gyrase C (small subunit) with moxifloxacin (MFX) revealed high binding affinity to wild type with considerably high Glide XP docking score of -7.88 kcal/mol. MFX affinity decreases toward single mutants and was minimum toward the DM with a docking score of -3.82 kcal/mol. Docking studies were also performed against 8-Methyl-moxifloxacin which exhibited higher binding affinity against wild and mutants DNA gyrase when compared to MFX. Molecular Mechanics/Generalized Born Surface Area method predicted the binding free energy of the wild, A90V, D94G, and DM complexes to be -55.81, -25.87, -20.45, and -12.29 kcal/mol, respectively. These complexes were further subjected to 30 ns long MD simulations to examine significant interactions and conformational flexibilities in terms of root mean square deviation, root mean square fluctuation, and strength of hydrogen bond formed. This comparative drug interaction analysis provides systematic insights into the mechanism behind drug resistance and also paves way toward identifying potent lead compounds that could combat drug resistance of DNA gyrase due to mutations.

Alanine mutation of the catalytic sites of Pantothenate Synthetase causes distinct conformational changes in the ATP binding region.

The enzyme Pantothenate synthetase (PS) represents a potential drug target in Mycobacterium tuberculosis. Its X-ray crystallographic structure has demonstrated the significance and importance of conserved active site residues including His44, His47, Asn69, Gln72, Lys160 and Gln164 in substrate binding and formation of pantoyl adenylate intermediate. In the current study, molecular mechanism of decreased affinity of the enzyme for ATP caused by alanine mutations was investigated using molecular dynamics (MD) simulations and free energy calculations. A total of seven systems including wild-type + ATP, H44A + ATP, H47A + ATP, N69A + ATP, Q72A + ATP, K160A + ATP and Q164A + ATP were subjected to 50 ns MD simulations. Docking score, MM-GBSA and interaction profile analysis showed weak interactions between ATP (substrate) and PS (enzyme) in H47A and H160A mutants as compared to wild-type, leading to reduced protein catalytic activity. However, principal component analysis (PCA) and free energy landscape (FEL) analysis revealed that ATP was strongly bound to the catalytic core of the wild-type, limiting its movement to form a stable complex as compared to mutants. The study will give insight about ATP binding to the PS at the atomic level and will facilitate in designing of non-reactive analogue of pantoyl adenylate which will act as a specific inhibitor for PS.