Extended-connectivity fingerprints (ECFPs) are a novel class of topological fingerprints for molecular characterization. Historically, topological fingerprints were developed for substructure and similarity searching. ECFPs were developed specifically for structure−activity modeling. ECFPs are circular fingerprints with a number of useful qualities: they can be very rapidly calculated; they are not predefined and can represent an essentially infinite number of different molecular features (including stereochemical information); their features represent the presence of particular substructures, allowing easier interpretation of analysis results; and the ECFP algorithm can be tailored to generate different types of circular fingerprints, optimized for different uses. While the use of ECFPs has been widely adopted and validated, a description of their implementation has not previously been presented in the literature.

Extended-Connectivity Fingerprints

The docking field has come of age. The time is ripe to present the principles of docking, reviewing the current state of the field. Two reasons are largely responsible for the maturity of the computational docking area. First, the early optimism that the very presence of the "correct" native conformation within the list of predicted docked conformations signals a near solution to the docking problem, has been replaced by the stark realization of the extreme difficulty of the next scoring/ranking step. Second, in the last couple of years more realistic approaches to handling molecular flexibility in docking schemes have emerged. As in folding, these derive from concepts abstracted from statistical mechanics, namely, populations. Docking and folding are interrelated. From the purely physical standpoint, binding and folding are analogous processes, with similar underlying principles. Computationally, the tools developed for docking will be tremendously useful for folding. For large, multidomain proteins, domain docking is probably the only rational way, mimicking the hierarchical nature of protein folding. The complexity of the problem is huge. Here we divide the computational docking problem into its two separate components. As in folding, solving the docking problem involves efficient search (and matching) algorithms, which cover the relevant conformational space, and selective scoring functions, which are both efficient and effectively discriminate between native and non-native solutions. It is universally recognized that docking of drugs is immensely important. However, protein-protein docking is equally so, relating to recognition, cellular pathways, and macromolecular assemblies. Proteins function when they are bound to other molecules. Consequently, we present the review from both the computational and the biological points of view. Although large, it covers only partially the extensive body of literature, relating to small (drug) and to large protein-protein molecule docking, to rigid and to flexible. Unfortunately, when reviewing these, a major difficulty in assessing the results is the non-uniformity in the formats in which they are presented in the literature. Consequently, we further propose a way to rectify it here.

Principles of docking: An overview of search algorithms and a guide to scoring functions

ed, together with any associated supplementary (deposited) data. The CSD itself acts as a computerized depository for large-volume numerical results for some 30 journals. A total of 584 primary sources are now referenced in the CSD, of which 74 are regularly scanned in-house to provide ca. 80% of current input. Remaining references are located via a scan of secondary sources, particularly Chemical Abstracts. Each entry in the CSD relates to a specific crystal structure determination of a specific chemical compound. Each entry is identified by a CSD reference code (REFCODE). This consists of eight characters: the first six are alphabetic and identify the chemical compound (initially assigned as a mnemonic of the compound name, now generated automatically for new compounds), the last two characters are digits which trace the publication history and define (a) whether the paper is a republication by the same authors (perhaps reporting an improved coordinate set) or (b) whether the paper is a redetermination by a different set of authors. The information recorded for each entry may conveniently be categorized according to its "dimensionality", as described below and illustrated in Figure 1. 1 D information consists of bibliographic and chemical text strings, together with certain individual numeric items: comBATCH OR VERSION 4 GRAPHICS VERSION 4 GRAPHICS

The development of versions 3 and 4 of the Cambridge Structural Database System

In this paper we describe the search strategies developed for docking flexible molecules to macomolecular sites that are incorporated into the widely distributed DOCK software, version 40 The search strategies include incremental construction and random conformation search and utilize the existing Coulombic and Lennard-Jones grid-based scoring function The incremental construction strategy is tested with a panel of 15 crystallographic testcases, created from 12 unique complexes whose ligands vary in size and flexibility For all testcases, at least one docked position is generated within 2 A of the crystallographic position For 7 of 15 testcases, the top scoring position is also within 2 A of the crystallographic position The algorithm is fast enough to successfully dock a few testcases within seconds and most within 100 s The incremental construction and the random search strategy are evaluated as database docking techniques with a database of 51 molecules docked to two of the crystallographic testcases Incremental construction outperforms random search and is fast enough to reliably rank the database of compounds within 15 s per molecule on an SGI R10000 cpu

/pdf/dock-4-0-search-strategies-for-automated-molecular-docking-2q6d5287ox.pdf

DOCK 4.0: Search strategies for automated molecular docking of flexible molecule databases

Most drugs have been discovered in random screens or by exploiting information about macromolecular receptors One source of this information is in the structures of critical proteins and nucleic acids The structure-based approach to design couples this information with specialized computer programs to propose novel enzyme inhibitors and other therapeutic agents Iterated design cycles have produced compounds now in clinical trials The combination of molecular structure determination and computation is emerging as an important tool for drug development These ideas will be applied to acquired immunodeficiency syndrome (AIDS) and bacterial drug resistance

https://science.sciencemag.org/content/sci/257/5073/1078.full.pdf

Structure-based strategies for drug design and discovery.

3DSEARCH: a system for three-dimensional substructure searching

Using CONCORD to construct a large database of three-dimensional coordinates from connection tables

We present some new ideas for characterizing and comparing largechemical databases. The comparison of the contents of large databases is nottrivial since it implies pairwise comparison of hundreds of thousands ofcompounds. We have developed methods for categorizing compounds into groupsor series based on their ring-system content, using precalculatedstructure-based hashcodes. Two large databases can then be compared bysimply comparing their hashcode tables. Furthermore, the number of distinctring-system combinations can be used as an indicator of database diversity.We also present an indepen- dent technique for diversity assessment calledthe ’saturation diversity‘ approach. This method is based on picking as manymutually dissimilar compounds as possible from a database or a subsetthereof. We show that both methods yield similar results. Since the twomethods measure very different properties, this probably says more about theproperties of the databases studied than about the methods.

Database diversity assessment: new ideas, concepts, and tools.

We address the problem of designing a general-purpose combinatorial library to screen for pharmaceutical leads. Conventional approaches focus on diversity as the primary factor in designing such libraries. We suggest making screening libraries out of a set of pharmaceutically relevant scaffolds, with multiple analogs per scaffold. The rationale for this rests on the fact that even though the hit-rate in active series is much higher than in the database as a whole, often a large fraction of the compounds in active series are inactive. This is especially true when the series has not been optimized for the target under study. We introduce the concept of ”hit-rate within a series“ and use historic screening data to arrive at a crude estimate for it. We then use simple probability arguments to show that 50-100 compounds are required in each series in order to be nearly certain of finding at least one active compound in each true active series for any given target.

Kevin S. Haraki

Papers

3DSEARCH: a system for three-dimensional substructure searching

Using CONCORD to construct a large database of three-dimensional coordinates from connection tables

Database diversity assessment: new ideas, concepts, and tools.

A novel approach to combinatorial library design.

Looking for pharmacophores in 3-D databases: Does conformational searching improve the yield of actives?