Computation in BioInformatics. Группа авторов
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are used for drawing chemical molecule.
1.2.6 QSAR (Quantitative Structure-Activity Relationship)
It is a statistical approach which attempts to correlate relationships between physical and chemical properties of molecules to their biological activities. QSAR predicts the molecular properties from their structure without any need to perform the experiment using in vitro or in vivo. This method saves time and resources [39]. Descriptors which are commonly used are number of rotatable bonds LogP and molecular weight (MW). This approach is used in optimizing lead which is the most important step of discovering drugs. The two techniques in 3D QSAR developed for LBDD are comparative molecular field analysis (CoMFA) and Comparative molecular similarity indices analysis (CoMSIA). Based on the data dimensions many QSAR approaches range from 1D QSAR to 6D QSAR.
a) CoMFA (Comparative Molecular Field Analysis)
It is categorized as 3D QSAR computational technique in which incorporation of experimental activities (log units of KI or IC 50) and the 3D structures of the molecules are done in the study. For this study, a set of derivatives of bioactive compounds having different substitutions is first selected. All of these compounds are then distributed into 30% test set and 70% training set. For QSAR performance, several softwares are available. An important aspect in CoMFA analysis is that it requires a common substructure with good alignment having the same conformation in all molecules.
b) CoMSIA (Comparative Molecular Similarity Indices Analysis)
It is a more advanced method of CoMFA, having fewer limitations. In this approach, SEAL similarity method is used as descriptors. Some of the descriptors used in this method are steric, electrostatic, hydrophobic, and hydrogen bonding. In the ligand binding areas, the unfavored region or the favored regions are indicated by generated contours. Sybyl-X 2.0 and E-Dragon are the software used for QSAR studies.
OCHEM: It is a web-based platform which aims to automate and simplify the typical steps that are required for QSAR modeling. It performs all the steps of a typical modeling workflow and provides facilities to use these data in the modeling process. It can be accessed at https://ochem.eu/home/show.do.
Discovery Studio: This software helps in analyzing the molecular structures/sequences and modeling it. It provides tools for performing analysis of basic data including functionality for editing and viewing data. It is a free viewer which can be used to open data generated by other softwares in the Discovery Studio. It can be downloaded from https://www.3dsbiovia.com/products/collaborative-science/bio-via-discovery-studio/visualization-download.php.
1.2.7 Pharmacophore Modeling
This is a powerful method which can easily categorize a group of molecules/ligands on the basis of active and inactive compounds. They provide set of molecular characteristics that is essential for the macromolecular recognition of ligands triggering a biological reaction. Some of the essential features modeled in pharmacophore are aromatic, hydrophobic, hydrogen bond acceptor (HBA), hydrogen bond donor (HBD), and anion and cation residues. Two main types of Pharmacophore modeling are structure-based modeling and ligand-based modeling.
Structure-based Pharmacophore modeling depends on the 3D structure of the protein obtained from PDB. These structures in PDB are provided by X-ray crystallography technique and/or NMR spectroscopy techniques. In the absence of 3D structure of protein, ligand-based Pharmacophore modeling is performed. Some of the softwares which are used for pharmacophore modeling are HypoGen, HipHop, DISCO, and PHASE.
PHASE: It is a user friendly pharmacophore modeling solution for LBDD and SBDD. It creates hypotheses from protein-ligand complexes and apo proteins with Schrödinger’s unique e-Pharmacophores technology. It can be accessed at https://www.schrodinger.com › phase.
1.2.8 Solubility of Molecule
Once the above steps have been done, the prospective compound is checked for whether the compound is water soluble or readily soluble in lipid which will affect the entry of the cells. The ability of a drug to make entrance into the cell and to bind to the target is an important factor which will determine its potency.
SwissADME: This web tool can analyze drug-likeness and pharmacokinetics of molecules. It evaluates the affability of small molecules in order to compute the physicochemistry of one or several small molecules. It can be easily accessed at http://www.swissadme.ch/index.php.
1.2.9 Molecular Dynamic Simulation
It is a computational method which involves the solution of Newton’s equation for motion to examine the dynamicity of the biological macromolecules. It provides comprehensive information on the fluctuations and conformational changes of proteins and nucleic acids. It helps in understanding the constancy of complexes of protein-ligand or of individual protein. Docking of protein-ligand complex with the ideal binding affinity is usually subjected to MD simulation. The protein topology is initially obtained by standard parameters using GROMACS or LEAP program. Online server PRODRG program is used for generating ligand topology [42]. It allows the study of interactions which occurs between different macromolecules during various cellular life processes and also analyzing of biological processes occurring in a living system. GROMACS is one of the most commonly used MD simulation softwares [43]. It produces trajectory files which carries the information of every conformational change that would have occurred on each atom during simulation. It provides a platform for the researchers to study the stability and minimization of energy of proteins as well as protein bound complexes. Some of software packages like NAMD, GROMACS, CHARMM, and AMBER are used for molecular dynamic simulation [44].
GROMACS: It is one of the most commonly used molecular dynamic simulation softwares. Input files are taken in PDB format which then produces trajectory files that carry the information of each and every conformational changes taking place that would have occurred on each atom during simulation. It requires several commands to process this software. Using this software, researchers are able to study the stability and minimization of energy of proteins as well as protein bound complexes. It can be downloaded from http://www.gromacs.org.
1.2.10 ADME Prediction
It plays an important role in the process of drug discovery. Most drugs with poor pharmacokinetic and toxicity predictions fail in the clinical trials. The toxicity and the molecular property are important properties in a drug whose prediction will help in determining the positivity or negativity of the drug during clinical trials. This method of prediction follows Lipinski’s rule of five [45]. The Lipinski’s rule of five states that HBAs must be less than 10, HBDs must be less than 5, MW of the ligand must not be more than 500 Daltons; the number of rotatable bonds should be less than 10 and the milogP value must be less than five. The Lipinski’s rule accepts compounds with one violation and those satisfying these rules can be orally available for humans. Softwares like PreADMET, VolSurf, admet-SAR, QikProp, PASS, and Molinspiration are used for ADME prediction [46, 47].