Salma Jamal

Molecular principles behind pyrazinamide resistance due to mutations in panD gene in Mycobacterium tuberculosis.

The latest resurrection of drug resistance poses serious threat to the treatment and control of the disease. Mutations have been detected in panD gene in the Mycobacterium tuberculosis (Mtb) strains. Mutation of histidine to arginine at residue 21 (H21R) and isoleucine to valine at residue 29 (I49V) in the non-active site of panD gene has led to PZA resistance. This study will help in reconnoitering the mechanism of pyrazinamide (PZA) resistance caused due to double mutation identified in the panD gene of M. tuberculosis clinical isolates. It is known that panD gene encodes aspartate decarboxylase essential for β-alanine synthesis that makes it a potential therapeutic drug target for tuberculosis treatment. The knowledge about the molecular mechanism conferring drug resistance in M. tuberculosis is scarce, which is a significant challenge in designing successful therapeutic drug. In this study, structural and dynamic repercussions of H21R-I49V double mutation in panD complexed with PZA have been corroborated through docking and molecular dynamics based simulation. The double mutant (DM) shows low docking score and thus, low binding affinity for PZA as compared to the native protein. It was observed that the mutant protein exhibits more structural fluctuation at the ligand binding site in comparison to the native type. Furthermore, the flexibility and compactness analyses indicate that the double mutation influence interaction of PZA with the protein. The hydrogen-bond interaction patterns further supported our results. The covariance and PCA analysis elucidated that the double mutation affects the collective motion of residues in phase space. The results have been presented with an explanation for the induced drug resistance conferred by the H21R-I49V double mutation in panD gene and gain valuable insight to facilitate the advent of efficient therapeutics for combating resistance against PZA.

Hydrophobic Interactions Are a Key to MDM2 Inhibition by Polyphenols as Revealed by Molecular Dynamics Simulations and MM/PBSA Free Energy Calculations

p53, a tumor suppressor protein, has been proven to regulate the cell cycle, apoptosis, and DNA repair to prevent malignant transformation. MDM2 regulates activity of p53 and inhibits its binding to DNA. In the present study, we elucidated the MDM2 inhibition potential of polyphenols (Apigenin, Fisetin, Galangin and Luteolin) by MD simulation and MM/PBSA free energy calculations. All polyphenols bind to hydrophobic groove of MDM2 and the binding was found to be stable throughout MD simulation. Luteolin showed the highest negative binding free energy value of -173.80 kJ/mol followed by Fisetin with value of -172.25 kJ/mol. It was found by free energy calculations, that hydrophobic interactions (vdW energy) have major contribution in binding free energy.

Hsp90: Friends, clients and natural foes

Hsp90, a homodimeric ATPase, is responsible for the correct folding of a number of newly synthesized polypeptides in addition to the correct folding of denatured/misfolded client proteins. It requires several co-chaperones and other partner proteins for chaperone activity. Due to the involvement of Hsp90-dependent client proteins in a variety of oncogenic signaling pathways, Hsp90 inhibition has emerged as one of the leading strategies for anticancer chemotherapeutics. Most of Hsp90 inhibitors blocks the N terminal ATP binding pocket and prevents the conformational changes which are essential for the loading of co-chaperones and client proteins. Several other inhibitors have also been reported which disrupt chaperone cycle in ways other than binding to N terminal ATP binding pocket. The Hsp90 inhibition is associated with heat shock response, mediated by HSF-1, to overcome the loss of Hsp90 and sustain cell survival. This review is an attempt to give an over view of all the important players of chaperone cycle.

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

BackgroundThe 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.ResultsTwo 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.ConclusionIn 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

BackgroundThe 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.ResultsThe 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).ConclusionAnalysis 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.

Fragment based G-QSAR and molecular dynamics based mechanistic simulations into hydroxamic-based HDAC inhibitors against spinocerebellar ataxia

Expansion of polyglutamine (CAG) triplets within the coding gene ataxin 2 results in transcriptional repression, forming the molecular basis of the neurodegenerative disorder named spinocerebellar ataxia type-2 (SCA2). HDAC inhibitors (HDACi) have been elements of great interest in polyglutamine disorders such as Huntington’s and Ataxia’s. In this study, we have selected hydroxamic acid derivatives as HDACi and performed fragment-based G-QSAR, molecular docking studies and molecular dynamics simulations for elucidating the dynamic mode of action of HDACi with His-Asp catalytic dyad of HDAC4. The model was statistically validated to establish its predictive robustness. The model was statistically significant with r2 value of .6297, cross-validated co-relation coefficient q2 value of .5905 and pred_r2 (predicted square co-relation coefficient) value of .85. An F-test value of 56.11 confirms absolute robustness of the model. Two combinatorial libraries comprising of 3180 compounds were created with hydroxamate moiety as the template and their pIC50 activities were predicted based on the G-QSAR model. The combinatorial library created was screened on the basis of predicted activity (pIC50), with two resultant top scoring compounds, HIC and DHC. The interaction of the compounds with His-Asp dyad in terms of H-bond interactions with His802, Asp840, Pro942, and Gly975 residues of HDAC4 was evaluated by docking and 20 ns long molecular dynamics simulations. This study provides valuable leads for structural substitutions required for hydroxamate moiety to exhibit enhanced inhibitory activity against HDAC4. The reported compounds demonstrated good binding and thus can be considered as potent therapeutic leads against ataxia.

Molecular principles behind Boceprevir resistance due to mutations in hepatitis C NS3/4A protease

The hepatitis C virus (HCV) infection is a primary cause of chronic hepatitis which eventually progresses to cirrhosis and in some instances might advance to hepatocellular carcinoma. According to the WHO report, HCV infects 130-150 million people globally and every year 350,000 to 500,000 people die from hepatitis C virus infection. Great achievement has been made in viral treatment evolution, after the development of HCV NS3/4A protease inhibitor (Boceprevir). However, efficacy of Boceprevir is compromised by the emergence of drug resistant variants. The molecular principle behind drug resistance of the protease mutants such as (V36M, T54S and R155K) is still poorly understood. Therefore in this study, we employed a series of computational strategies to analyze the binding of antiviral drug, Boceprevir to HCV NS3/4A protease mutants. Our results clearly demonstrate that the point mutations (V36M, T54S and R155K) in protease are associated with lowering of its binding affinity with Boceprevir. Exhaustive analysis of the simulated Boceprevir-bound wild and mutant complexes revealed variations in hydrophobic interactions, hydrogen bond occupancy and salt bridge interactions. Also, substrate envelope analysis scrutinized that the studied mutations reside outside the substrate envelope which may affect the Boceprevir affinity towards HCV protease but not the protease enzymatic activity. Furthermore, structural analyses of the binding site volume and flexibility show impairment in flexibility and stability of the binding site residues in mutant structures. In order to combat Boceprevir resistance, renovation of binding interactions between the drug and protease may be valuable. The structural insight from this study reveals the mechanism of the Boceprevir resistance and the results can be valuable for the design of new PIs with improved efficiency.

Identification of chebulinic acid as potent natural inhibitor of M. tuberculosis DNA gyrase and molecular insights into its binding mode of action

Drug resistant tuberculosis has threatened all the advances that have been made in TB control at the global stage in the last few decades. DNA gyrase enzymes are an excellent target for antibacterial drug discovery as they are involved in essential functions like DNA replication. Here we report, a successful application of high throughput virtual screening (HTVS) to identify an inhibitor of Mycobacterium DNA gyrase targeting the wild type and the most prevalent three double mutants of quinolone resistant DNA gyrase namely A90V+D94G, A74S+D94G and A90V+S91P. HTVS of 179.299 compounds gave five compounds with significant binding affinity. Extra presicion (XP) docking and MD simulations gave a clear view of their interaction pattern. Among them, chebulinic acid (CA), a phytocompound obtained from Terminalia chebula was the most potent inhibitor with significantly high XP docking score, -14.63, -16.46, -15.94 and -15.11 against wild type and three variants respectively. Simulation studies for a period of 16 ns indicated stable DNA gyrA-CA complex formation. This stable binding would result in inhibition of the enzyme by two mechanisms. Firstly, binding of CA causes displacement of catalytic Tyr129 away from its target DNA-phosphate molecule from 1.6 Å to 3.8-7.3 Å and secondly, by causing steric hindrance to the binding of DNA strand at DNA binding site of enzyme. The combined effect would result in loss of cleavage and religation activity of enzyme leading to bactericidal effect on tuberculosis. This phytocompound displays desirable quality for carrying forward as a lead compound for anti-tuberculosis drug development. The results presented here are solely based on computations and need to be validated experimentally in order to assert the proposed mechanism of action.

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.

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

BackgroundAlzheimer’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.ResultsIn 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.ConclusionsTo 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.