Untitled

Mills, James E.; Esch, Iwan J. P. de; Perkins, Tim D. J.; Dean, Philip M.

doi:10.1023/a:1011102129244

Cited by 35 publications

(18 citation statements)

References 29 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Since then many advances have taken place in automated methods which is reflected in the recent commercial programs like Distance Comparison (DISCO [31]), HipHop [32] (a part of CATALYST [30]), Genetic Algorithm Superposition Program (GASP [32]), Chem Diverse (3 and 4-point pharmacophore generation in Chem-X [43]), SLATE [44], MOLMOD [45], MIMIC [46], Mapping Pharamcophores In Ligands (MPHIL [47]), Dynamic Pharmacophore approach using molecular dynamics [48] and receptor guided approaches. DISCO, Catalyst and GASP are widely used for pharmacophore identification.…”

Section: Pharmacophore Methodsmentioning

confidence: 99%

Pharmacophore Modeling in Drug Discovery and Development: An Overview

Khedkar¹,

Malde²,

Coutinho³

et al. 2007

127

View full text Add to dashboard Cite

Pharmacophore mapping is one of the major elements of drug design in the absence of structural data of the target receptor. The tool initially applied to discovery of lead molecules now extends to lead optimization. Pharmacophores can be used as queries for retrieving potential leads from structural databases (lead discovery), for designing molecules with specific desired attributes (lead optimization), and for assessing similarity and diversity of molecules using pharmacophore fingerprints. It can also be used to align molecules based on the 3D arrangement of chemical features or to develop predictive 3D QSAR models. This review begins with a brief historical overview of the pharmacophore evolution followed by a coverage of the developments in methodologies for pharmacophore identification over the period from inception of the pharmacophore concept to recent developments of the more sophisticated tools such as Catalyst, GASP, and DISCO. In addition, we present some very recent successes of the widely used pharmacophore generation methods in drug discovery.

show abstract

Section: Pharmacophore Methodsmentioning

confidence: 99%

Pharmacophore Modeling in Drug Discovery and Development: An Overview

Khedkar¹,

Malde²,

Coutinho³

et al. 2007

127

View full text Add to dashboard Cite

show abstract

“…Many types of optimization methods have been used in structural alignment applications including simulated annealing. 2 It is assumed that the reader has some familiarity with simulated annealing algorithms 20 (outlined in Fig. 5), and this discussion will focus on where the Wah and Chen algorithm deviates from the classical simulated annealing approach.…”

Section: Simulated Annealingmentioning

confidence: 99%

“…The published record on the subject of flexible, molecular alignment is extensive, 2 and thorough reviews have been written. 1,3 Many of these alignment methodologies have proven valuable in drug design efforts, but none can lay claim to being superior in all cases.…”

Section: Introductionmentioning

confidence: 99%

The flexible alignment of molecular structures using simulated annealing with weighted Lagrangian multipliers

Raymond

Holsworth²,

Jalaie

2010

J Comput Chem

View full text Add to dashboard Cite

A framework for superimposing small molecules is presented. The proposed method consists of a simple atom-based, flexible alignment. The optimization procedure used in the alignment is based on a recently published variant of the simulated annealing whereby nonlinear constraints are accommodated using Lagrangian multipliers. It differs from other published superposition algorithms in that any number of nonlinear constraints can be readily imposed on the structural alignment directly through the objective function without assuming an a priori trade-off between competing conditions. These can include equality and equality constraints on distances, angles, and energy states. Examples illustrating the use of the proposed approach are also provided.

show abstract

“…This does not yield a complete picture of the site but identifies key hydrogen-bonding site points and lipophilic regions. An algorithm, SLATE, has been written [10] to optimise the match between partially similar flexible molecules. Optimum superpositions can be obtained for the site points projected away from the ligand surfaces.…”

Section: The Complementarity Of Ligand-based Approachesmentioning

confidence: 99%

Beyond the Genome: A Drug for Every Gene?

Bailey¹

2002

The Scientific World JOURNAL

View full text Add to dashboard Cite

Genomics is revolutionizing the way in which we think about biology. Downstream technologies such as proteomics and structural biology now underpin our understanding of biological structure and function, while genome-wide transcriptome and proteome analysis allow us to gain an impression of the dynamic processes underlying biochemistry and physiology. Nowhere is the impact of genomics greater than in drug discovery. Genomics is now influencing the evolution of the pharmaceutical industry. This presentation will focus on emerging technologies in genomics-based drug design and chemoinformatics as solutions for new lead discovery, the starting point of drug development. It will highlight some of the opportunities and challenges in industrializing the drug design process, and will address the emerging bottlenecks in reducing the design process to genome-wide application. The Importance of Genome-Wide Informatics in Target DiscoveryThe development of computational bioinformatics has been crucial to our understanding of the inter-relationships between specific therapeutic targets and the functional gene families to which they belong. The most comprehensive example of this has undoubtedly been the task of sequencing and assembling the human genome[1,2], a feat that lay at the very edge of our ability to handle such complex computational tasks. Assigning function to the individual genes within the genome is a continuing challenge.The information produced from both public and private genome programs already provides a powerful foundation for future exploitation of genes as targets in drug discovery [3] and comprehensive mining of the human genome for therapeutic targets has uncovered a wealth of new opportunities for exploitation in molecular pharmacology and mechanism-based drug discovery [4]. Traditional High-Throughput Screening Approaches for Lead DiscoveryUntil recently, the contribution made by genomics to drug discovery centred primarily on the production of protein targets for biochemical screening. With bioinformatics allowing the definition of specific therapeutically relevant genes and gene families, many targets have been reduced to discovery practice through high-throughput screening approaches.

show abstract

Untitled

Cited by 35 publications

References 29 publications

Pharmacophore Modeling in Drug Discovery and Development: An Overview

Pharmacophore Modeling in Drug Discovery and Development: An Overview

The flexible alignment of molecular structures using simulated annealing with weighted Lagrangian multipliers

Beyond the Genome: A Drug for Every Gene?

Contact Info

Product

Resources

About