Chemical Similarity Searching
TL;DR: The concept of similarity searching is introduced, differentiating it from the more common substructure searching, and the current generation of fragment-based measures that are used for searching chemical structure databases are discussed.
read more
Abstract: This paper reviews the use of similarity searching in chemical databases. It begins by introducing the concept of similarity searching, differentiating it from the more common substructure searching, and then discusses the current generation of fragment-based measures that are used for searching chemical structure databases. The next sections focus upon two of the principal characteristics of a similarity measure: the coefficient that is used to quantify the degree of structural resemblance between pairs of molecules and the structural representations that are used to characterize molecules that are being compared in a similarity calculation. New types of similarity measure are then compared with current approaches, and examples are given of several applications that are related to similarity searching.
read more
Chat with Paper
AI Agents for this Paper
Find similar papers on Google Scholar, PubMed and Arxiv
Write a critical review of this paper
Analyze citations of this paper to find unaddressed research gaps
Citations
Mini-fingerprints for virtual screening: design principles and generation of novel prototypes based on information theory.
TL;DR: The design of relatively simple fingerprints for the identification of molecules having similar biological activity and recognition of remote similarity relationships is investigated, and systematic evaluation of fingerprint performance in VS test calculations demonstrates that these new prototypes perform better than previously generated MFPs.
26
Computational Approaches for Decoding Select Odorant-Olfactory Receptor Interactions Using Mini-Virtual Screening.
K. Harini,Ramanathan Sowdhamini +1 more
TL;DR: This study revealed that homologous sequences with high sequence identity need not bind to the same/ similar ligand with a given affinity, which will be useful for expression and mutation studies on these receptors.
•Posted Content
What is known about Vertex Cover Kernelization
TL;DR: A survey on kernelization of the vertex cover problem can be found in this article, where the authors dedicate this survey to Professor Juraj Hromkovic on the occasion of his 60th birthday.
26
Deciphering the multicomponent synergy mechanism from a systems pharmacology perspective: Application to Gualou Xiebai Decoction for coronary heart disease
Yang Yang,Chao Huang,Xing Su,Jinglin Zhu,Xuetong Chen,Yingxue Fu,Zhenzhong Wang,Jun Zhou,Wei Xiao,Chunli Zheng,Yonghua Wang,Yonghua Wang +11 more
TL;DR: The integrated systems pharmacology method supplies accurate illustration of the molecular mechanisms of GXD to treat CHD and provides a new way for developing combination therapeutics.
26
A knowledge-based weighting approach to ligand-based virtual screening.
Nikolaus Stiefl,Andrea Zaliani +1 more
TL;DR: In this article, a straightforward weighting approach to include additional structural or SAR knowledge into reduced graphs was proposed, based on the recently introduced reduced graph concept of ErG (extending reduced graphs).
26
References
Hierarchical Grouping to Optimize an Objective Function
TL;DR: In this paper, a procedure for forming hierarchical groups of mutually exclusive subsets, each of which has members that are maximally similar with respect to specified characteristics, is suggested for use in large-scale (n > 100) studies when a precise optimal solution for a specified number of groups is not practical.
19.8K
Features of Similarity
TL;DR: The metric and dimensional assumptions that underlie the geometric representation of similarity are questioned on both theoretical and empirical grounds and a set of qualitative assumptions are shown to imply the contrast model, which expresses the similarity between objects as a linear combination of the measures of their common and distinctive features.
Development and validation of a genetic algorithm for flexible docking.
TL;DR: GOLD (Genetic Optimisation for Ligand Docking) is an automated ligand docking program that uses a genetic algorithm to explore the full range of ligand conformational flexibility with partial flexibility of the protein, and satisfies the fundamental requirement that the ligand must displace loosely bound water on binding.
6.5K
Comparative molecular field analysis (CoMFA). 1. Effect of shape on binding of steroids to carrier proteins.
TL;DR: The main features of the CoMFA approach, exemplified by analyses of the affinities of 21 varied steroids to corticosteroid and testosterone-binding globulins, and a number of advances in the methodology of molecular graphics are described.
3.8K
A Fast Flexible Docking Method using an Incremental Construction Algorithm
TL;DR: This work presents an automatic method for docking organic ligands into protein binding sites that combines an appropriate model of the physico-chemical properties of the docked molecules with efficient methods for sampling the conformational space of the ligand.
2.8K