Rao Sethumadhavan

In silico investigation of molecular mechanism of laminopathy caused by a point mutation (R482W) in lamin A/C protein.

Lamin A/C proteins are the major components of a thin proteinaceous filamentous meshwork, the lamina, that underlies the inner nuclear membrane. A few specific mutations in the lamin A/C gene cause a disease with remarkably different clinical features: FPLD, or familial partial lipodystrophy (Dunnigan-type), which mainly affects adipose tissue. Lamin A/C mutant R482W is the key variant that causes FPLD. Biomolecular interaction and molecular dynamics (MD) simulation analysis were performed to understand dynamic behavior of native and mutant structures at atomic level. Mutant lamin A/C (R482W) showed more interaction with its biological partners due to its expansion of interaction surface and flexible nature of binding residues than native lamin A/C. MD simulation clearly indicates that the flexibility of interacting residues of mutant are mainly due to less involvement in formation of inter and intramolecular hydrogen bonds. Our analysis of native and Mutant lamin A/C clearly shows that the structural and functional consequences of the mutation R482W causes FPLD. Because of the pivotal role of lamin A/C in maintaining dynamics of nuclear function, these differences likely contribute to or represent novel mechanisms in laminopathy development.

Drug resistance mechanism of PncA in Mycobacterium tuberculosis

Tuberculosis continues to be a global health threat. Pyrazinamide (PZA) is an important first-line drug in multidrug-resistant tuberculosis treatment. The emergence of strains resistant to PZA represents an important public health problem, as both first- and second-line treatment regimens include PZA. It becomes toxic to Mycobacterium tuberculosis when converted to pyrazinoic acid by the bacterial pyrazinamidase (PncA) enzyme. Resistance to PZA is caused mainly by the loss of enzyme activity by mutation, the mechanism of resistance is not completely understood. In our studies, we analysed three mutations (D8G, S104R and C138Y) of PncA which are involved in resistance towards PZA. Binding pocket analysis solvent accessibility analysis, molecular docking and interaction analysis were performed to understand the interaction behaviour of mutant enzymes with PZA. Molecular dynamics simulations were conducted to understand the three-dimensional (3D) conformational behaviour of native and mutants PncA. Our analysis clearly indicates that the mutation (D8G, S104R and C138Y) in PncA is responsible for rigid binding cavity which in turn abolishes conversion of PZA to its active form and is the sole reason for PZA resistance. Excessive hydrogen bonding between PZA binding cavity residues and their neighbouring residues are the reason of rigid binding cavity during simulation. We present an exhaustive analysis of the binding site flexibility and its 3D conformations that may serve as new starting points for structure-based drug design and helps the researchers to design new inhibitors with consideration of rigid criterion of binding residues due to mutation of this essential target. An animated Interactive 3D Complement (I3DC) is available in Proteopedia at http://proteopedia.org/w/Journal:JBSD:11

Studies on Adaptability of Binding Residues Flap Region of TMC-114 Resistance HIV-1 Protease Mutants

Abstract Drug resistant mutations have severely restricted the success of HIV therapy. These mutations frequently involve the aspartic protease encoded by the virus. Knowledge of the molecular mechanisms underlying the conformational changes of HIV-1 protease mutants may be useful in developing more ffective and longer lasting treatment regimes. The flap regions of the protease are the target of a particular type of mutations occurring far from the active site, which are able to produce significant resistance against the anti-HIV drug TMC-114. We provide insight into the molecular basis of TMC-114 resistance major flap mutations (I50V and I54M) in HIV-1 protease. It reports the shape complementarity and receptor-ligand interaction analysis supported by unrestrained all-atom molecular dynamics simulations of wild and major flap mutants of HIV-1 protease that sample large conformational changes of the flaps and active site binding residues. Both resistant flap mutants showed less atomic interaction toward TMC-114 and more structural deviation compared to wild HIV-protease. It is due to increasing flexibility at TMC-114 binding cavity and deviation of binding residues in 3-D space. Distortion in binding cavity and deviation in binding residues are the result of alteration in hydrogen bonding. Flap region also exhibited similar behaviour due to changes in number of hydrogen bonds during simulations.

Structural basis for the resilience of Darunavir (TMC114) resistance major flap mutations of HIV-1 protease

To understand the origin of the apparent low sensitivity to mutations exhibited by Darunavir, the binding energetics of this inhibitor to the HIV-1 protease was studied. Our research indicates that the observed effectiveness of Darunavir against the wild type HIV-1 protease is due to an extremely high affinity towards the wild-type and a relatively mild effect to the I50V and I54M mutations is due to low affinity towards the inhibitor. Good affinity of Darunavir accounts for the additive effects of well accommodation at binding site, good ligand-receptor electrostatic and van der waals energy while, the low susceptibility to I50V and I54M can be rationalized in terms of flexibility in the binding site residues that do not permit drug accommodation to the binding site distortions created by the mutation. The major flap mutations I50V and I54M lower the binding affinity of Darunavir by altering the position of binding site residues in 3D space. It decreases the electrostatic and van der waals interaction energy and further reduction in total receptor-ligand interaction energy. The results summarized in this paper emphasize the importance of shape complementarity and protein flexibility analysis of binding residual interactions in drug design. These data together with an interaction energy and flexibility analysis have established rigorous guidelines for the design of new and more powerful inhibitors. The principles learned from the HIV-1 protease can be applied to other design problems.

A novel computational and structural analysis of nsSNPs in CFTR gene

Single Nucleotide Polymorphisms (SNPs) are being intensively studied to understand the biological basis of complex traits and diseases. The Genetics of human phenotype variation could be understood by knowing the functions of SNPs. In this study using computational methods, we analyzed the genetic variations that can alter the expression and function of the CFTR gene responsible candidate for causing cystic fibrosis. We applied an evolutionary perspective to screen the SNPs using a sequence homology-based SIFT tool, which suggested that 17 nsSNPs (44%) were found to be deleterious. The structure-based approach PolyPhen server suggested that 26 nsSNPS (66%) may disrupt protein function and structure. The PupaSuite tool predicted the phenotypic effect of SNPs on the structure and function of the affected protein. Structure analysis was carried out with the major mutation that occurred in the native protein coded by CFTR gene, and which is at amino acid position F508C for nsSNP with id (rs1800093). The amino acid residues in the native and mutant modeled protein were further analyzed for solvent accessibility, secondary structure and stabilizing residues to check the stability of the proteins. The SNPs were further subjected to iHAP analysis to identify htSNPs, and we report potential candidates for future studies on CFTR mutations.

CEP proteins: the knights of centrosome dynasty

Centrosome forms the backbone of cell cycle progression mechanism. Recent debates have occurred regarding the essentiality of centrosome in cell cycle regulation. CEP family protein is the active component of centrosome and plays a vital role in centriole biogenesis and cell cycle progression control. A total of 31 proteins have been categorized into CEP family protein category and many more are under candidate evaluation. Furthermore, by the recent advancements in genomics and proteomics researches, several new CEP proteins have also been characterized. Here we have summarized the importance of CEP family proteins and their regulation mechanism involved in proper cell cycle progression. Further, we have reviewed the detailed molecular mechanism behind the associated pathological phenotypes and the possible therapeutic approaches. Proteins such as CEP57, CEP63, CEP152, CEP164, and CEP215 have been extensively studied with a detailed description of their molecular mechanisms, which are among the primary targets for drug discovery. Moreover, CEP27, CEP55, CEP70, CEP110, CEP120, CEP135, CEP192, CEP250, CEP290, and CEP350 also seem promising for future drug discovery approaches. Since the overview implicates that the overall researches on CEP proteins are not yet able to present significant details required for effective therapeutics development, thus, it is timely to discuss the importance of future investigations in this field.

Effect of deleterious nsSNP on the HER2 receptor based on stability and binding affinity with herceptin: a computational approach.

In this study, we identified the most deleterious non-synonymous SNP of ERBB2 (HER2) receptors by its stability and investigated its binding affinity with herceptin. Out of 135 SNPs, 10 are nsSNPs in the coding region, in which one of the nsSNP (SNPid rs4252633) is commonly found to be damaged by I-Mutant 2.0, SIFT and PolyPhen servers. With this effort, we modelled the mutant HER2 protein based on this deleterious nsSNP (rs4252633). The modeled mutant showed less stability than native HER 2 protein, based on both total energy of the mutant and stabilizing residues in the mutant protein. This is due to a deviation between the mutant and the native HER2, having an RMSD of about 2.81 A. Furthermore, we compared the binding efficiency of herceptin with native and mutant HER2 receptors. We found that herceptin has a high binding affinity with mutant HER2 receptor, with a binding energy of -24.40 kcal/mol, as compared to the native type, which has a binding energy of -15.26 kcal/mol due to six-hydrogen bonding and two salt bridges exist between herceptin and the mutant type, whereas the native type establishes four hydrogen bonds and two salt bridges with herceptin. This analysis portrays that mutant type has two additional hydrogen bonds with herceptin compared with the native type. Normal mode analysis also showed that the two amino acids, namely Asp596 and Glu598 of mutant HER2, forming additional hydrogen bonding with herceptin, had a slightly higher flexibility than the native type. Based on our investigations, we propose that SNPid rs4252633 could be the most deleterious nsSNP for HER2 receptor, and that herceptin could be the best drug for mutant compared to the native HER2 target.

AKT Kinase Pathway: A Leading Target in Cancer Research

AKT1, a serine/threonine-protein kinase also known as AKT kinase, is involved in the regulation of various signalling downstream pathways including metabolism, cell proliferation, survival, growth, and angiogenesis. The AKT kinases pathway stands among the most important components of cell proliferation mechanism. Several approaches have been implemented to design an efficient drug molecule to target AKT kinases, although the promising results have not been confirmed. In this paper we have documented the detailed molecular insight of AKT kinase protein and proposed a probable doxorubicin based approach in inhibiting miR-21 based cancer cell proliferation. Moreover, the inhibition of miR-21 activation by raising the FOXO3A concentration seems promising in reducing miR-21 mediated cancer activation in cell. Furthermore, the use of next generation sequencing and computational drug design approaches will greatly assist in designing a potent drug molecule against the associated cancer cases.

Exploring the environmental preference of weak interactions in (α/β)8 barrel proteins

The environmental preference for the occurrence of noncanonical hydrogen bonding and cation–π interactions, in a data set containing 71 nonredundant (α/β)8 barrel proteins, with respect to amino acid type, secondary structure, solvent accessibility, and stabilizing residues has been performed. Our analysis reveals some important findings, which include (a) higher contribution of weak interactions mediated by main‐chain atoms irrespective of the amino acids involved; (b) domination of the aromatic amino acids among interactions involving side‐chain atoms; (c) involvement of strands as the principal secondary structural unit, accommodating cross strand ion pair interaction and clustering of aromatic amino acid residues; (d) significant contribution to weak interactions occur in the solvent exposed areas of the protein; (e) majority of the interactions involve long‐range contacts; (f) the preference of Arg is higher than Lys to form cation–π interaction; and (g) probability of theoretically predicted stabilizing amino acid residues involved in weak interaction is higher for polar amino acids such as Trp, Glu, and Gln. On the whole, the present study reveals that the weak interactions contribute to the global stability of (α/β)8 TIM‐barrel proteins in an environment‐specific manner, which can possibly be exploited for protein engineering applications. Proteins 2006.

Computational SNP Analysis: Current Approaches and Future Prospects

The computational approaches in determining disease-associated Non-synonymous single nucleotide polymorphisms (nsSNPs) have evolved very rapidly. Large number of deleterious and disease-associated nsSNP detection tools have been developed in last decade showing high prediction reliability. Despite of all these highly efficient tools, we still lack the accuracy level in determining the genotype–phenotype association of predicted nsSNPs. Furthermore, there are enormous questions that are yet to be computationally compiled before we might talk about the prediction accuracy. Earlier we have incorporated molecular dynamics simulation approaches to foster the accuracy level of computational nsSNP analysis roadmap, which further helped us to determine the changes in the protein phenotype associated with the computationally predicted disease-associated mutation. Here we have discussed on the present scenario of computational nsSNP characterization technique and some of the questions that are crucial for the proper understanding of pathogenicity level for any disease associated mutations.