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Computational drug design

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https://www.readbyqxmd.com/read/28238723/non-steroidal-anti-inflammatory-drugs-are-caspase-inhibitors
#1
Christina E Smith, Subada Soti, Torey A Jones, Akihisa Nakagawa, Ding Xue, Hang Yin
Non-steroidal anti-inflammatory drugs (NSAIDs) are among the most commonly used drugs in the world. While the role of NSAIDs as cyclooxygenase (COX) inhibitors is well established, other targets may contribute to anti-inflammation. Here we report caspases as a new pharmacological target for NSAID family drugs such as ibuprofen, naproxen, and ketorolac at physiologic concentrations both in vitro and in vivo. We characterize caspase activity in both in vitro and in cell culture, and combine computational modeling and biophysical analysis to determine the mechanism of action...
February 15, 2017: Cell Chemical Biology
https://www.readbyqxmd.com/read/28236243/identifying-loop-mediated-protein-protein-interactions-using-loopfinder
#2
Timothy R Siegert, Michael Bird, Joshua A Kritzer
Peptides are an increasingly useful class of molecules, finding unique applications as chemical probes and potential drugs. They are particularly adept at inhibiting protein-protein interactions, which are often difficult to target using small molecules. The identification and rational design of protein-binding epitopes remains a bottleneck in the development of bioactive peptides. One fruitful strategy has been using structured scaffolds to present essential hot spot residues involved in protein-protein recognition, and this process has been greatly advanced by computational tools that can identify hot spot residues...
2017: Methods in Molecular Biology
https://www.readbyqxmd.com/read/28236238/flexible-backbone-methods-for-predicting-and-designing-peptide-specificity
#3
Noah Ollikainen
Protein-protein interactions play critical roles in essentially every cellular process. These interactions are often mediated by protein interaction domains that enable proteins to recognize their interaction partners, often by binding to short peptide motifs. For example, PDZ domains, which are among the most common protein interaction domains in the human proteome, recognize specific linear peptide sequences that are often at the C-terminus of other proteins. Determining the set of peptide sequences that a protein interaction domain binds, or it's "peptide specificity," is crucial for understanding its cellular function, and predicting how mutations impact peptide specificity is important for elucidating the mechanisms underlying human diseases...
2017: Methods in Molecular Biology
https://www.readbyqxmd.com/read/28236237/modeling-peptide-protein-structure-and-binding-using-monte-carlo-sampling-approaches-rosetta-flexpepdock-and-flexpepbind
#4
Nawsad Alam, Ora Schueler-Furman
Many signaling and regulatory processes involve peptide-mediated protein interactions, i.e., the binding of a short stretch in one protein to a domain in its partner. Computational tools that generate accurate models of peptide-receptor structures and binding improve characterization and manipulation of known interactions, help to discover yet unknown peptide-protein interactions and networks, and bring into reach the design of peptide-based drugs for targeting specific systems of medical interest.Here, we present a concise overview of the Rosetta FlexPepDock protocol and its derivatives that we have developed for the structure-based characterization of peptide-protein binding...
2017: Methods in Molecular Biology
https://www.readbyqxmd.com/read/28235665/an-in-silico-approach-to-find-a-peptidomimetic-targeting-extracellular-domain-of-her3-from-a-her3-nanobody
#5
Z Pourhashem, M Mehrpouya, N Yardehnavi, A Eslamparast, F Kazemi-Lomedasht
HER3 is an important therapeutic target in cancer treatments. HER3 Nanobodies (Nbs) are a novel class of antibodies with several competitive advantages over conventional antibodies. A peptidomimetic derived from these Nbs can be considered to be a small peptide mimicking some of the molecular recognition interactions of a natural peptide or protein in a three-dimensional (3D) space, with a receptor that has improved properties. In this study, we introduce a new approach to design a peptidomimetic derived from HER3 Nb through an in silico analysis...
February 10, 2017: Computational Biology and Chemistry
https://www.readbyqxmd.com/read/28228926/antibody-h3-structure-prediction
#6
REVIEW
C Marks, C M Deane
Antibodies are proteins of the immune system that are able to bind to a huge variety of different substances, making them attractive candidates for therapeutic applications. Antibody structures have the potential to be useful during drug development, allowing the implementation of rational design procedures. The most challenging part of the antibody structure to experimentally determine or model is the H3 loop, which in addition is often the most important region in an antibody's binding site. This review summarises the approaches used so far in the pursuit of accurate computational H3 structure prediction...
2017: Computational and Structural Biotechnology Journal
https://www.readbyqxmd.com/read/28224490/predicting-beta-barrel-transmembrane-proteins-using-hmms
#7
Georgios N Tsaousis, Stavros J Hamodrakas, Pantelis G Bagos
Transmembrane beta-barrels (TMBBs) constitute an important structural class of membrane proteins located in the outer membrane of gram-negative bacteria, and in the outer membrane of chloroplasts and mitochondria. They are involved in a wide variety of cellular functions and the prediction of their transmembrane topology, as well as their discrimination in newly sequenced genomes is of great importance as they are promising targets for antimicrobial drugs and vaccines. Several methods have been applied for the prediction of the transmembrane segments and the topology of beta barrel transmembrane proteins utilizing different algorithmic techniques...
2017: Methods in Molecular Biology
https://www.readbyqxmd.com/read/28221002/computational-biology-and-chemistry-in-mti-emphasis-on-the-prediction-of-some-admet-properties
#8
REVIEW
Maria A Miteva, Bruno O Villoutreix
Our research and teaching group called MTi (Molécules Thérapeutiques in silico) has developed numerous applications available online, thanks to the RPBS platform (Ressource Parisienne en Bioinformatique Structurale), in the field of chemoinformatics, structural bioinformatics and drug design. Since its opening in 2009, over 200 articles/reviews have been reported and involve virtual screening studies, prediction of druggability, analysis of protein-protein interaction inhibitors, development of databases, data mining and knowledge discovery, as well as combined in silico-in vitro work to search for new hits and chemical probes acting on original targets in several therapeutic areas...
February 21, 2017: Molecular Informatics
https://www.readbyqxmd.com/read/28205401/computer-aided-drug-design-to-explore-cyclodextrin-therapeutics-and-biomedical-applications
#9
Azizeh Abdolmaleki, Fatemeh Ghasemi, Jahan B Ghasemi
Cyclodextrin (CD) is a subset of the macrocyclic structural class, which is an important class of small organic agents that are useful functional excipients. They have wide range application possibilities in different fields of sciences such as material preparation, medicine, analytical chemistry, and separation processes. They are used widely in pharmaceutical formulations and drug delivery for increasing the water solubility of low soluble drugs and drug candidates. Due to the ring structure, they behave differently than smaller molecules and may be capable of hitting new classes of targets...
February 2017: Chemical Biology & Drug Design
https://www.readbyqxmd.com/read/28204845/mirnas-target-databases-developmental-methods-and-target-identification-techniques-with-functional-annotations
#10
REVIEW
Nagendra Kumar Singh
PURPOSE: microRNA (miRNA) regulates diverse biological mechanisms and metabolisms in plants and animals. Thus, the discoveries of miRNA has revolutionized the life sciences and medical research.The miRNA represses and cleaves the targeted mRNA by binding perfect or near perfect or imperfect complementary base pairs by RNA-induced silencing complex (RISC) formation during biogenesis process. One miRNA interacts with one or more mRNA genes and vice versa, hence takes part in causing various diseases...
February 15, 2017: Cellular and Molecular Life Sciences: CMLS
https://www.readbyqxmd.com/read/28198675/predicting-disease-related-genes-using-integrated-biomedical-networks
#11
Jiajie Peng, Kun Bai, Xuequn Shang, Guohua Wang, Hansheng Xue, Shuilin Jin, Liang Cheng, Yadong Wang, Jin Chen
BACKGROUND: Identifying the genes associated to human diseases is crucial for disease diagnosis and drug design. Computational approaches, esp. the network-based approaches, have been recently developed to identify disease-related genes effectively from the existing biomedical networks. Meanwhile, the advance in biotechnology enables researchers to produce multi-omics data, enriching our understanding on human diseases, and revealing the complex relationships between genes and diseases...
January 25, 2017: BMC Genomics
https://www.readbyqxmd.com/read/28194627/fragment-based-in-silico-modeling-of-multi-target-inhibitors-against-breast-cancer-related-proteins
#12
Alejandro Speck-Planche, M Natália D S Cordeiro
Breast cancer is the most frequent cancer reported in women, being responsible for hundreds of thousands of deaths. Chemotherapy has proven to be effective against this malignant neoplasm depending on different biological factors such as the histopathology, grade, and stage, among others. However, breast cancer cells have become resistant to current chemotherapeutic regimens, urging the discovery of new anti-breast cancer drugs. Computational approaches have the potential to offer promising alternatives to accelerate the search for potent and versatile anti-breast cancer agents...
February 13, 2017: Molecular Diversity
https://www.readbyqxmd.com/read/28191464/construction-of-multilevel-structure-for-avian-influenza-virus-system-based-on-granular-computing
#13
Yang Li, Qi-Hao Liang, Meng-Meng Sun, Xu-Qing Tang, Ping Zhu
Exploring the genetic structure of influenza viruses attracts the attention in the field of molecular ecology and medical genetics, whose epidemics cause morbidity and mortality worldwide. The rapid variations in RNA strand and changes of protein structure of the virus result in low-accuracy subtyping identification and make it difficult to develop effective drugs and vaccine. This paper constructs the evolutionary structure of avian influenza virus system considering both hemagglutinin and neuraminidase protein fragments...
2017: BioMed Research International
https://www.readbyqxmd.com/read/28186913/a-stochastic-spiking-neural-network-for-virtual-screening
#14
A Morro, V Canals, A Oliver, M L Alomar, F Galan-Prado, P J Ballester, J L Rossello
Virtual screening (VS) has become a key computational tool in early drug design and screening performance is of high relevance due to the large volume of data that must be processed to identify molecules with the sought activity-related pattern. At the same time, the hardware implementations of spiking neural networks (SNNs) arise as an emerging computing technique that can be applied to parallelize processes that normally present a high cost in terms of computing time and power. Consequently, SNN represents an attractive alternative to perform time-consuming processing tasks, such as VS...
February 7, 2017: IEEE Transactions on Neural Networks and Learning Systems
https://www.readbyqxmd.com/read/28185290/computational-analysis-of-the-human-sinus-node-action-potential-model-development-and-effects-of-mutations
#15
Alan Fabbri, Matteo Fantini, Ronald Wilders, Stefano Severi
The sinoatrial node (SAN) is the normal pacemaker of the mammalian heart.  Over several decades, a large amount of data on the ionic mechanisms underlying the spontaneous electrical activity of SAN pacemaker cells has been obtained, mostly in experiments on single cells isolated from rabbit SAN. This wealth of data has allowed the development of mathematical models of the electrical activity of rabbit SAN pacemaker cells. Our aim was to construct a more comprehensive model of the electrical activity of a human SAN pacemaker cell, using recently obtained electrophysiological data from human SAN pacemaker cells...
February 9, 2017: Journal of Physiology
https://www.readbyqxmd.com/read/28185116/potential-acetylcholinesterase-inhibitors-molecular-docking-molecular-dynamics-and-in-silico-prediction
#16
Alessandra S Kiametis, Mônica A Silva, Luiz A S Romeiro, João B L Martins, Ricardo Gargano
This paper deals with molecular modeling of new therapeutic agents for treating the Alzheimer's disease. The therapeutic line adopted for this study is the cholinergic hypothesis. To modulate positively the cholinergic function through the inhibition of the acetylcholinesterase, a set of candidates was designed from a natural compound extracted from the cashew nutshell liquid, anacardic acid. In silico screening of this chemical library revealed a ligand that is more promising once it is correlated with an active drug through specific topological and electronic descriptors...
February 2017: Journal of Molecular Modeling
https://www.readbyqxmd.com/read/28182403/forging-the-basis-for-developing-protein-ligand-interaction-scoring-functions
#17
Zhihai Liu, Minyi Su, Li Han, Jie Liu, Qifan Yang, Yan Li, Renxiao Wang
In structure-based drug design, scoring functions are widely used for fast evaluation of protein-ligand interactions. They are often applied in combination with molecular docking and de novo design methods. Since the early 1990s, a whole spectrum of protein-ligand interaction scoring functions have been developed. Regardless of their technical difference, scoring functions all need data sets combining protein-ligand complex structures and binding affinity data for parametrization and validation. However, data sets of this kind used to be rather limited in terms of size and quality...
February 9, 2017: Accounts of Chemical Research
https://www.readbyqxmd.com/read/28182187/multiscale-modeling-of-plasmonic-enhanced-energy-transfer-and-cavitation-around-laser-excited-nanoparticles
#18
Adrien Dagallier, Etienne Boulais, Christos Boutopoulos, Rémi Lachaine, Michel Meunier
Nanoscale bubbles generated around laser-excited metallic nanoparticles are promising candidates for targeted drug and gene delivery in living cells. The development of new nanomaterials for efficient nanobubble-based therapy is however limited by the lack of reliable computational approaches for the prediction of their size and dynamics, due to the wide range of time and space scales involved. In this work, we present a multiscale modeling framework that segregates the various channels of plasmon de-excitation and energy transfer to describe the generation and dynamics of plasmonic nanobubbles...
February 9, 2017: Nanoscale
https://www.readbyqxmd.com/read/28179976/biobetters-from-an-integrated-computational-experimental-approach
#19
REVIEW
Serdar Kuyucak, Veysel Kayser
Biobetters are new drugs designed from existing peptide or protein-based therapeutics by improving their properties such as affinity and selectivity for the target epitope, and stability against degradation. Computational methods can play a key role in such design problems-by predicting the changes that are most likely to succeed, they can drastically reduce the number of experiments to be performed. Here we discuss the computational and experimental methods commonly used in drug design problems, focusing on the inverse relationship between the two, namely, the more accurate the computational predictions means the less experimental effort is needed for testing...
2017: Computational and Structural Biotechnology Journal
https://www.readbyqxmd.com/read/28176631/grid-based-continual-analysis-of-molecular-interior-for-drug-discovery-qsar-and-qspr
#20
A V Potemkin, M A Grishina, V A Potemkin
BACKGROUND: In 1979, R.D.Cramer and M.Milne made a first realization of the above mentioned principles attempting to compare molecules by aligning them in space and by mapping their molecular fields to a 3D grid. Further, this approach was developed as the DYLOMMS (DYnamic Lattice-Oriented Molecular Modelling System) approach. In 1984, H.Wold and S.Wold proposed the use of partial least squares (PLS) analysis, instead of principal component analysis, to correlate the field values with biological activities...
February 7, 2017: Current Drug Discovery Technologies
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