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A Frame Work for Learning Drug Designing through Molecular Modelling Software Techniques and Biological Databases for Protein-Ligand Interactions

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TLDR
This review outlines the major tools for protein - ligand docking which in turn emphasize the importance of molecular docking in modern drug discovery process.
Abstract
Applications of computer and information technology are indispensable in various fields especially in the field of biology. The use of computer aided tools plays a key role in solving biological problems. The spontaneous process of molecular docking is important for finding potentially strong candidate of drug for various viruses. The binding of protein receptors with ligand molecules is essential in drug discovery process. The aim of molecular docking tools is to predict the interaction between protein and ligand. This review outlines the major tools for protein - ligand docking which in turn emphasize the importance of molecular docking in modern drug discovery process.

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Citations
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Prediction of Drug–Target Interaction Networks from the Integration of Protein Sequences and Drug Chemical Structures

TL;DR: A novel computational approach based on protein sequence, namely PDTPS (Predicting Drug Targets with Protein Sequence) to predict DTI is proposed, which has good prediction performance and is a useful tool and suitable for predicting DTI, as well as other bioinformatics tasks.
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High Performance Parallel Computing with Cloud Technologies

TL;DR: This paper would discuss large scale data analysis using different implementations on the above mentioned tools and after that it would give a performance analysis of these tools on the given implementation like Cap3, HEP, Cloudburst.
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Review of NEDDylation inhibition activity detection methods

TL;DR: This review will provide an up-to-date and comprehensive review of the methods for detecting NEDDylation activity that will contribute to NEDdylation inhibitor development.
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Contexts enabled Decision Making using sensors to perceive pervasive environment

TL;DR: This work assists to combine various basic low level contexts to provide reliable decision making in the pervasive environment using sensor networks and context aware computing to bring automated decision making along with accuracy information.
References
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Journal ArticleDOI

Experimental and computational approaches to estimate solubility and permeability in drug discovery and development settings

TL;DR: Experimental and computational approaches to estimate solubility and permeability in discovery and development settings are described in this article, where the rule of 5 is used to predict poor absorption or permeability when there are more than 5 H-bond donors, 10 Hbond acceptors, and the calculated Log P (CLogP) is greater than 5 (or MlogP > 415).
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SWISS-MODEL and the Swiss-PdbViewer: an environment for comparative protein modeling.

Nicolas Guex, +1 more
- 01 Jan 1997 - 
TL;DR: An environment for comparative protein modeling is developed that consists of SWISS‐MODEL, a server for automated comparativeprotein modeling and of the SWiss‐PdbViewer, a sequence to structure workbench that provides a large selection of structure analysis and display tools.
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LIGPLOT: a program to generate schematic diagrams of protein-ligand interactions

TL;DR: The LIGPLOT program automatically generates schematic 2-D representations of protein-ligand complexes from standard Protein Data Bank file input giving a simple and informative representation of the intermolecular interactions and their strengths, including hydrogen bonds, hydrophobic interactions and atom accessibilities.
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The Universal Protein Resource (UniProt)

TL;DR: During 2004, tens of thousands of Knowledgebase records got manually annotated or updated; the UniProt keyword list got augmented by additional keywords; the documentation of the keywords and are continuously overhauling and standardizing the annotation of post-translational modifications.
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The evolving role of natural products in drug discovery

TL;DR: Recent technological advances that help to address issues such as the lack of compatibility of traditional natural-product extract libraries with high-throughput screening and unrealized expectations from current lead-generation strategies have led to a renewed interest in natural products in drug discovery.
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