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Computational Biology and Chemistry

Agnieszka Mickiewicz, Joanna Sarzyńska, Maciej Miłostan, Anna Kurzyńska-Kokorniak, Agnieszka Rybarczyk, Piotr Łukasiak, Tadeusz Kuliński, Marek Figlerowicz, Jacek Błażewicz
Plant Dicer-like proteins (DCLs) belong to the Ribonuclease III (RNase III) enzyme family. They are involved in the regulation of gene expression and antiviral defense through RNA interference pathways. A model plant, Arabidopsis thaliana encodes four DCL proteins (AtDCL1-4) that produce different classes of small regulatory RNAs. Our studies focus on AtDCL4 that processes double-stranded RNAs (dsRNAs) into 21 nucleotide trans-acting small interfering RNAs. So far, little is known about the structures of plant DCLs and the complexes they form with dsRNA...
November 17, 2016: Computational Biology and Chemistry
Wei Zhou, Yan Zhang, Yue-Hua Li, Shuang Wang, Jing-Jing Zhang, Cui-Xia Zhang, Zhi-Sheng Zhang
OBJECTIVE: This work aimed to identify dysregulated pathways for Staphylococcus aureus (SA) exposed macrophages based on pathway interaction network (PIN). METHODS: The inference of dysregulated pathways was comprised of four steps: preparing gene expression data, protein-protein interaction (PPI) data and pathway data; constructing a PIN dependent on the data and Pearson correlation coefficient (PCC); selecting seed pathway from PIN by computing activity score for each pathway according to principal component analysis (PCA) method; and investigating dysregulated pathways in a minimum set of pathways (MSP) utilizing seed pathway and the area under the receiver operating characteristics curve (AUC) index implemented in support vector machines (SVM) model...
November 13, 2016: Computational Biology and Chemistry
Masaki Banno, Yusuke Komiyama, Wei Cao, Yuya Oku, Kokoro Ueki, Kazuya Sumikoshi, Shugo Nakamura, Tohru Terada, Kentaro Shimizu
Several methods have been proposed for protein-sugar binding site prediction using machine learning algorithms. However, they are not effective to learn various properties of binding site residues caused by various interactions between proteins and sugars. In this study, we classified sugars into acidic and nonacidic sugars and showed that their binding sites have different amino acid occurrence frequencies. By using this result, we developed sugar-binding residue predictors dedicated to the two classes of sugars: an acid sugar binding predictor and a nonacidic sugar binding predictor...
November 9, 2016: Computational Biology and Chemistry
Perla Lucía Ordóñez-Baquera, Everardo González-Rodríguez, Gerardo Armando Aguado-Santacruz, Quintín Rascón-Cruz, Ana Conesa, Verónica Moreno-Brito, Raquel Echavarria, Joel Dominguez-Viveros
BACKGROUND: MicroRNAs (miRNAs) are small non-coding RNA molecules that regulate signal transduction, development, metabolism, and stress responses in plants through post-transcriptional degradation and/or translational repression of target mRNAs. Several studies have addressed the role of miRNAs in model plant species, but miRNA expression and function in economically important forage crops, such as Bouteloua gracilis (Poaceae), a high-quality and drought-resistant grass distributed in semiarid regions of the United States and northern Mexico remain unknown...
November 9, 2016: Computational Biology and Chemistry
G Koteswara Reddy, K Nagamalleswara Rao, Kiran Yarrakula
The gene 30S ribosomal protein S2 (30S2) is identified as a potential drug and vaccine target for Pneumonia. Its structural characterization is an important to understand the mechanism of action for identifying its receptor and/or other binding partners. The comparative genomics and proteomics studies are useful for structural characterization of 30S2 in C. Pneumoniae using different bioinformatics tools and web servers. In this study, the protein 30S2 structure was modelled and validated by Ramachandran plot...
November 9, 2016: Computational Biology and Chemistry
Achintya Mohan Goswami
Malaria remains one of the most serious infectious diseases in the world. There are five human species of the Plasmodium genus, of which Plasmodium falciparum is the most virulent and responsible for the vast majority of malaria related deaths. The unique biochemical processes that exist in Plasmodium falciparum provide a useful way to develop novel inhibitors. One such biochemical pathway is the methyl erythritol phosphate pathway (MEP), required to synthesize isoprenoid precursors. In the present study, a detailed computational analysis has been performed for 1-deoxy-d-xylulose-5-phosphate synthase, a key enzyme in MEP...
November 5, 2016: Computational Biology and Chemistry
Shihai Yan, Lishan Yao, Baotao Kang, Jin Yong Lee
The hydrogen bond plays a vital role in structural arrangement, intermediate state stabilization, materials function, and biological activity of certain enzymatic reactions. The solvent and electronic effects on hydrogen bonds are illustrated employing the polarizable contimuum model at B3LYP/6-311++G(d,p) level. Geometry optimizations reflect the significant solvent and electronic effect. The proton departs spontaneously upon oxidation from the hydroxyl group of tyrosyl in hydrogen bonded Tyr⋯Asp⋯Arg triads in both gas phase and solvents...
November 2, 2016: Computational Biology and Chemistry
Venura Herath
Dehydration-responsive element- (DREB) proteins are considered as the master regulators of plant abiotic stress responses including drought, salinity and cold. They are also involved in other developmental processes such as embryo and endosperm development. DREB family of transcription factors consist of two sub families namely CBF1/DREB1 and DREB2. In this study, a genome-wide in silico analysis was carried out to dissect the structure and function of DREB2 family transcription factors in the rice genome. Using Arabidopsis DREB2 sequences a total of five rice DREB2 homologs were identified and they were distributed among four chromosomes...
October 29, 2016: Computational Biology and Chemistry
Davorka R Jandrlić
At present, there are a number of methods for the prediction of T-cell epitopes and major histocompatibility complex (MHC)-binding peptides. Despite numerous methods for predicting T-cell epitopes, there still exist limitations that affect the reliability of prevailing methods. For this reason, the development of models with high accuracy are crucial. An accurate prediction of the peptides that bind to specific major histocompatibility complex class I and II (MHC-I and MHC-II) molecules is important for an understanding of the functioning of the immune system and the development of peptide-based vaccines...
October 27, 2016: Computational Biology and Chemistry
Boudour Khabou, Olfa Siala-Sahnoun, Lamia Gargouri, Emna Mkaouar-Rebai, Leila Keskes, Mongia Hachicha, Faiza Fakhfakh
Progressive Familial Intrahepatic Cholestasis type 3 (PFIC3) is an autosomal-recessive liver disease due to mutations in the ABCB4 gene encoding for the MDR3 protein. In the present study, we performed molecular and bioinformatic analyses in PFIC3 patients in order to understand the molecular basis of the disease. The three studied patients with PFIC3 were screened by PCR amplification followed by direct sequencing of the 27 coding exons of ABCB4. In silico analysis was performed by bioinformatic programs. We revealed three synonymous polymorphisms c...
October 22, 2016: Computational Biology and Chemistry
Manijeh Mahdavi, Violaine Moreau
Antigenic peptides or cancer peptide vaccines can be directly delivered to cancer patients to produce immunologic responses against cancer cells. Specifically, designed peptides can associate with Major Histocompatibility Complex (MHC) class I or II molecules on the cell surface of antigen presenting cells activating anti-tumor effector mechanisms by triggering helper T cell (Th) or cytotoxic T cells (CTL). In general, high binding to MHCs approximately correlates with in vivo immunogenicity. Consequently, a molecular docking technique was run on a library of novel discontinuous peptides predicted by PEPOP from Human epidermal growth factor receptor 2 (HER2 ECD) subdomain III...
October 19, 2016: Computational Biology and Chemistry
Xin Geng, Jiaogen Zhou, Jihong Guan
The significant improvement of KE07 series in catalytic activities shows the great success of computational design approaches combined with directed evolution in protein design. Understanding the protein dynamics in the evolutionary optimization process of computationally designed enzyme will provide profound implication to study enzyme function and guide protein design. Here, side chain squared generalized order parameters and entropy of each protein are calculated using 50ns molecular dynamics simulation data in both apo and bound states...
October 15, 2016: Computational Biology and Chemistry
Seema Patel
Hepatitis C (HCV) is a deadly virus from family Flaviviridae, causing acute or chronic liver inflammation. Given its lethality and no known vaccine to curb it, understanding its pathogenic mechanism is critical. By analyzing the domains in its protein sequence, a plethora can be learnt about its immune manipulation strategies. In this regard, current in silico study compares publicly-available HCV polyprotein sequences and their domain profiles. Apart from using UniProt sequences and SMART (Simple modular architecture research tool) platform for domain profiling, a set of customized scripts were developed to extract the patterns of protein domain distribution...
October 15, 2016: Computational Biology and Chemistry
Pradipta Ranjan Rauta, Sarbani Ashe, Debasis Nayak, Bismita Nayak
Virulence-related outer membrane proteins (Omps) are expressed in bacteria (Gram-negative) such as V. cholerae and are vital to bacterial invasion in to eukaryotic cell and survival within macrophages that could be best candidate for development of vaccine against V. cholerae. Applying in silico approaches, the 3-D model of the Omp was developed using Swiss model server and validated byProSA and Procheck web server. The continuous stretch of amino acid sequences 26mer: RTRSNSGLLTWGDKQTITLEYGDPAL and 31mer: FFAGGDNNLRGYGYKSISPQDASGALTGAKY having B-cell binding sites were selected from sequence alignment after B cell epitopes prediction by BCPred and AAP prediction modules of BCPreds...
October 12, 2016: Computational Biology and Chemistry
Zhong Ni, Xiting Wang, Tianchen Zhang, Rong Zhong Jin
Anaplastic lymphoma kinase (ALK) has become as an important target for the treatment of various human cancers, especially non-small-cell lung cancer. A mutation, F1174C, suited in the C-terminal helix αC of ALK and distal from the small-molecule inhibitor ceritinib bound to the ATP-binding site, causes the emergence of drug resistance to ceritinib. However, the detailed mechanism for the allosteric effect of F1174C resistance mutation to ceritinib remains unclear. Here, molecular dynamics (MD) simulations and binding free energy calculations [Molecular Mechanics/Generalized Born Surface Area (MM/GBSA)] were carried out to explore the advent of drug resistance mutation in ALK...
October 11, 2016: Computational Biology and Chemistry
Money Gupta, Rashi Chauhan, Yamuna Prasad, Gulshan Wadhwa, Chakresh Kumar Jain
The lack of complete treatments and appearance of multiple drug-resistance strains of Burkholderia cepacia complex (Bcc) are causing an increased risk of lung infections in cystic fibrosis patients. Bcc infection is a big risk to human health and demands an urgent need to identify new therapeutics against these bacteria. Network biology has emerged as one of the prospective hope in identifying novel drug targets and hits. We have applied protein-protein interaction methodology to identify new drug-target candidates (orthologs) in Burkhloderia cepacia GG4, which is an important strain for studying the quorum-sensing phenomena...
October 8, 2016: Computational Biology and Chemistry
Seketoulie Keretsu, Rosy Sarmah
: Protein complex detection from protein-protein interaction (PPI) network has received a lot of focus in recent years. A number of methods identify protein complexes as dense sub-graphs using network information while several other methods detect protein complexes based on topological information. While the methods based on identifying dense sub-graphs are more effective in identifying protein complexes, not all protein complexes have high density. Moreover, existing methods focus more on static PPI networks and usually overlook the dynamic nature of protein complexes...
October 8, 2016: Computational Biology and Chemistry
Mohammad Uzzal Hossain, Arafat Rahman Oany, Shah Adil Ishtiyaq Ahmad, Md Anayet Hasan, Md Arif Khan, Md Al Ahad Siddikey
Chagas is a parasitic disease with major threat to public health due to its resistance against commonly available drugs. Trypanothione reductase (TryR) is the key enzyme to develop this disease. Though this enzyme is well thought-out as potential drug target, the accurate structure of enzyme-inhibitor complex is required to design a potential inhibitor which is less available for TryR. In this research, we aimed to investigate the advanced drug over the available existing drugs by designing inhibitors as well as to identify a new enzyme-inhibitor complex that may act as a template for drug design...
October 7, 2016: Computational Biology and Chemistry
David Agustriawan, Chien-Hung Huang, Jim Jinn-Chyuan Sheu, Shan-Chih Lee, Jeffrey J P Tsai, Nilubon Kurubanjerdjit, Ka-Lok Ng
Epigenetic regulation has been linked to the initiation and progression of cancer. Aberrant expression of microRNAs (miRNAs) is one such mechanism that can activate or silence oncogenes (OCGs) and tumor suppressor genes (TSGs) in cells. A growing number of studies suggest that miRNA expression can be regulated by methylation modification, thus triggering cancer development. However, there is no comprehensive in silico study concerning miRNA regulation by direct DNA methylation in cancer. Ovarian serous cystadenocarcinoma (OSC) was therefore chosen as a tumor model for the present work...
October 1, 2016: Computational Biology and Chemistry
Renu Vyas, Sanket Bapat, Esha Jain, Muthukumarasamy Karthikeyan, Sanjeev Tambe, Bhaskar D Kulkarni
In order to understand the molecular mechanism underlying any disease, knowledge about the interacting proteins in the disease pathway is essential. The number of revealed protein-protein interactions (PPI) is still very limited compared to the available protein sequences of different organisms. Experiment based high-throughput technologies though provide some data about these interactions, those are often fairly noisy. Computational techniques for predicting protein-protein interactions therefore assume significance...
September 30, 2016: Computational Biology and Chemistry
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