Novel drug design and bioinformatics: an introduction

2021 ◽  
Vol 0 (0) ◽  
Author(s):  
Mohammad Kalim Ahmad Khan ◽  
Salman Akhtar
Keyword(s):  
Drug Design ◽  
Target Identification ◽  
Homology Modelling ◽  
3D Structure ◽  
Cost Effective ◽  
Biological Data ◽  
Combinatorial Design ◽  
Ligand Docking ◽  
Structure Based Drug Design ◽  
Biological Targets

Abstract In the current era of high-throughput technology, where enormous amounts of biological data are generated day by day via various sequencing projects, thereby the staggering volume of biological targets deciphered. The discovery of new chemical entities and bioisosteres of relatively low molecular weight has been gaining high momentum in the pharmacopoeia, and traditional combinatorial design wherein chemical structure is used as an initial template for enhancing efficacy pharmacokinetic selectivity properties. Once the compound is identified, it undergoes ADMET filtration to ensure whether it has toxic and mutagenic properties or not. If the compound has no toxicity and mutagenicity is either considered a potential lead molecule. Understanding the mechanism of lead molecules with various biological targets is imperative to advance related functions for drug discovery and development. Notwithstanding, a tedious and costly process, taking around 10–15 years and costing around $4 billion, cascaded approached of Bioinformatics and Computational biology viz., structure-based drug design (SBDD) and cognate ligand-based drug design (LBDD) respectively rely on the availability of 3D structure of target biomacromolecules and vice versa has made this process easy and approachable. SBDD encompasses homology modelling, ligand docking, fragment-based drug design and molecular dynamics, while LBDD deals with pharmacophore mapping, QSAR, and similarity search. All the computational methods discussed herein, whether for target identification or novel ligand discovery, continuously evolve and facilitate cost-effective and reliable outcomes in an era of overwhelming data.

Combined approach of homology modeling, molecular dynamics, and docking: computer-aided drug discovery

2019 ◽  
Vol 4 (10) ◽  
Author(s):  
Varun Chahal ◽  
Sonam Nirwan ◽  
Rita Kakkar
Keyword(s):  
Drug Design ◽  
Homology Modeling ◽  
3D Structure ◽  
Structure Based Drug Design ◽  
Combined Application ◽  
Cytoplasmic Proteins ◽  
Software Algorithms ◽  
Computer Aided ◽  
Drug Designing ◽  
Process Structure

Abstract With the continuous development in software, algorithms, and increase in computer speed, the field of computer-aided drug design has been witnessing reduction in the time and cost of the drug designing process. Structure based drug design (SBDD), which is based on the 3D structure of the enzyme, is helping in proposing novel inhibitors. Although a number of crystal structures are available in various repositories, there are various proteins whose experimental crystallization is difficult. In such cases, homology modeling, along with the combined application of MD and docking, helps in establishing a reliable 3D structure that can be used for SBDD. In this review, we have reported recent works, which have employed these three techniques for generating structures and further proposing novel inhibitors, for cytoplasmic proteins, membrane proteins, and metal containing proteins. Also, we have discussed these techniques in brief in terms of the theory involved and the various software employed. Hence, this review can give a brief idea about using these tools specifically for a particular problem.

scholarly journals Structure-Based Drug Design for Cytochrome P450 Family 1 Inhibitors

2018 ◽  
Vol 2018 ◽  
pp. 1-21 ◽  
Author(s):  
Zbigniew Dutkiewicz ◽  
Renata Mikstacka
Keyword(s):  
Drug Design ◽  
Active Sites ◽  
Wide Spectrum ◽  
Cytochromes P450 ◽  
Cancer Chemoprevention ◽  
Ligand Docking ◽  
Current Status ◽  
Structure Based Drug Design ◽  
Cytochrome P450 Family ◽  
Distinctive Role

Cytochromes P450 are a class of metalloproteins which are responsible for electron transfer in a wide spectrum of reactions including metabolic biotransformation of endogenous and exogenous substrates. The superfamily of cytochromes P450 consists of families and subfamilies which are characterized by a specific structure and substrate specificity. Cytochromes P450 family 1 (CYP1s) play a distinctive role in the metabolism of drugs and chemical procarcinogens. In recent decades, these hemoproteins have been intensively studied with the use of computational methods which have been recently developed remarkably to be used in the process of drug design by the virtual screening of compounds in order to find agents with desired properties. Moreover, the molecular modeling of proteins and ligand docking to their active sites provide an insight into the mechanism of enzyme action and enable us to predict the sites of drug metabolism. The review presents the current status of knowledge about the use of the computational approach in studies of ligand-enzyme interactions for CYP1s. Research on the metabolism of substrates and inhibitors of CYP1s and on the selectivity of their action is particularly valuable from the viewpoint of cancer chemoprevention, chemotherapy, and drug-drug interactions.

scholarly journals Cyanide Hydratase Modification Using Computational Design and Docking Analysis for Improved Binding Affinity in Cyanide Detoxification

Molecules ◽  
2021 ◽  
Vol 26 (6) ◽  
pp. 1799
Author(s):  
Narges Malmir ◽  
Najaf Allahyari Fard ◽  
Yamkela Mgwatyu ◽  
Lukhanyo Mekuto
Keyword(s):  
Trichoderma Harzianum ◽  
Homology Modelling ◽  
3D Structure ◽  
Design Procedure ◽  
Computational Design ◽  
Ligand Docking ◽  
Nucleophilic Attack ◽  
Total Charge ◽  
Ligand Complex ◽  
Cyanide Hydratase

Cyanide is a hazardous and detrimental chemical that causes the inactivation of the respiration system through the inactivation of cytochrome c oxidase. Because of the limitation in the number of cyanide-degrading enzymes, there is a great demand to design and introduce new enzymes with better functionality. This study developed an integrated method of protein-homology-modelling and ligand-docking protein-design approaches that reconstructs a better active site from cyanide hydratase (CHT) structure. Designing a mutant CHT (mCHT) can improve the CHT performance. A computational design procedure that focuses on mutation for constructing a new model of cyanide hydratase with better activity was used. In fact, this study predicted the three-dimensional (3D) structure of CHT for subsequent analysis. Inducing mutation on CHT of Trichoderma harzianum was performed and molecular docking was used to compare protein interaction with cyanide as a ligand in both CHT and mCHT. By combining multiple designed mutations, a significant improvement in docking for CHT was obtained. The results demonstrate computational capabilities for enhancing and accelerating enzyme activity. The result of sequence alignment and homology modeling show that catalytic triad (Cys-Glu-Lys) was conserved in CHT of Trichoderma harzianum. By inducing mutation in CHT structure, MolDock score enhanced from −18.1752 to −23.8575, thus the nucleophilic attack can occur rapidly by adding Cys in the catalytic cavity and the total charge of protein in pH 6.5 is increased from −6.0004 to −5.0004. Also, molecular dynamic simulation shows a stable protein-ligand complex model. These changes would help in the cyanide degradation process by mCHT.

scholarly journals Ligand docking and binding site analysis with pymol and autodock/vina

2015 ◽  
Vol 4 (2) ◽  
pp. 168 ◽  
Author(s):  
Mohd. Ahmar Rauf ◽  
Swaleha Zubair ◽  
Asim Azhar
Keyword(s):  
Molecular Docking ◽  
Drug Design ◽  
Three Dimensional ◽  
Structural Features ◽  
Docking Studies ◽  
Ligand Docking ◽  
Structure Based Drug Design ◽  
Site Analysis ◽  
User Friendly ◽  
Autodock 4.2

<p>Docking of various therapeutically important chemical entities to the specific target sites offers a meaningful strategy that may have tremendous scope in a drug design process. For a thorough understanding of the structural features that determine the strength of bonding between a ligand with its receptor, an insight to visualize binding geometries and interaction is mandatory. Bioinformatical as well as graphical software ‘PyMOL’ in combination with the molecular docking suites Autodock and Vina allows the study of molecular combination to visualize and understand the structure-based drug design efforts. In the present study, we outlined a user friendly method to perform molecular docking using vina and finally the results were analyzed in pymol in both two as well as three-dimensional orientation. The operation bypasses the steps that are involved in docking using cygwin terminal like formation of gpf and dpf files. The simple and straight-forward operation method does not require formal bioinformatics training to apprehend molecular docking studies using AutoDock 4.2 program.</p>

scholarly journals Use of computer in drug design and drug discovery: A review

2012 ◽  
Vol 1 (2) ◽  
Author(s):  
Md Mofizur Rahman ◽  
Md Rezaul Karim ◽  
Md Qamrul Ahsan ◽  
Abul Bashar Ripon Khalipha ◽  
Mohammed Raihan Chowdhury ◽  
...  
Keyword(s):  
Drug Design ◽  
Dna Cleavage ◽  
Cost Effective ◽  
Cancer Disease ◽  
Computer Aided Drug Design ◽  
Structure Based Drug Design ◽  
Software Libraries ◽  
Computer Aided ◽  
Modeling Software ◽  
Data Collections

Drug design through computer, a recent, very effective technique in modern arena. Now a days Computer Aided Drug Design (CADD) technologies are used in nanotechnology, molecular biology, biochemistry etc. The main benefit of the CADD is cost effective in research and development of drugs. There are wide ranges of software are used in CADD, Grid computing, window based general PBPK/PD modeling software, PKUDDS for structure based drug design,APIS, JAVA, Perl and Python, CADD as well as software including software libraries. There are different techniques used in CADD visualization, homology, molecular dynamic, energy minimization molecular docking, QSAR etc. Computer aided drug design is applicable in Cancer disease, transportation of drug to specific site in body, data collections and storages of organics and biologicals. Conformational properties and energetics of small molecules and DNA cleavage, molecular diagnostics based on fluorescences are focusing using this technique. DOI: http://dx.doi.org/10.3329/ijpls.v1i2.12955 International Journal of Pharmaceutical and Life Sciences Vol.1(2) 2012

scholarly journals Predicting the structure and energetics of protein-ligand interaction

2019 ◽  
Author(s):  
◽  
Zhiwei Ma
Keyword(s):  
Molecular Docking ◽  
Drug Design ◽  
Large Scale ◽  
Kinase Inhibitors ◽  
Ligand Docking ◽  
Pose Prediction ◽  
Computer Algorithms ◽  
Ligand Interaction ◽  
Structure Based Drug Design ◽  
Ligand Selectivity

Molecular docking has been a crucial component and remains a highly active area in computer-aided drug design (CADD). In simple terms, molecular docking uses computer algorithms to identify the "best" match between two molecules, a process analogous to solving three-dimensional jigsaw puzzles. In more rigorous terms, the molecular docking problem can be defined as predicting the "correct" bound association state for the given atomic coordinates of two molecules. Docking is an important tool for structure and affinity predictions of molecular association, which would lead to the mechanistic understanding of the physicochemical interactions at the atomic level. Protein-small molecule (referred to as "ligand") docking, in particular, has broad application to structure-based drug design, as drug compounds are usually small molecules. In this dissertation, I present my studies on protein-ligand docking. In the background introduction, I reviewed the docking methodology and the key recent developments in the field. Next, I applied an ensemble docking algorithm onto 14 protein kinases to study ligand selectivity, a major issue for the development of kinase inhibitors as anticancer drugs. In Chapter 3, I developed a web server for automated, in silico screening of multiple targets for a given ligand query. Finally, I integrated the new methods for protein-ligand binding mode prediction and applied the integrated method to a large-scale, blind prediction competition named Continuous Evaluation of Ligand Pose Prediction (CELPP).

Evaluation of Grey Wolf Optimization Algorithm on Rigid and Flexible Receptor Docking

2020 ◽  
Author(s):  
Kin Meng Wong ◽  
Shirley Siu
Keyword(s):  
Scoring Function ◽  
Ligand Docking ◽  
Receptor Protein ◽  
Pose Prediction ◽  
Grey Wolf ◽  
Success Rates ◽  
Autodock Vina ◽  
Grey Wolf Optimization ◽  
Structure Based Drug Design ◽  
Docking Program

Protein-ligand docking programs are indispensable tools for predicting the binding pose of a ligand to the receptor protein in current structure-based drug design. In this paper, we evaluate the performance of grey wolf optimization (GWO) in protein-ligand docking. Two versions of the GWO docking program – the original GWO and the modified one with random walk – were implemented based on AutoDock Vina. Our rigid docking experiments show that the GWO programs have enhanced exploration capability leading to significant speedup in the search while maintaining comparable binding pose prediction accuracy to AutoDock Vina. For flexible receptor docking, the GWO methods are competitive in pose ranking but lower in success rates than AutoDockFR. Successful redocking of all the flexible cases to their holo structures reveals that inaccurate scoring function and lack of proper treatment of backbone are the major causes of docking failures.

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