Computer-Aided Design of Fragment Mixtures for NMR-Based Screening

Abstract

Fragment-based drug discovery is widely applied both in industrial and in academic screening programs. Several screening techniques rely on NMR to detect binding of a fragment to a target. NMR-based methods are among the most sensitive techniques and have the further advantage of yielding a low rate of false positives and negatives. However, NMR is intrinsically slower than other screening techniques; thus, to increase throughput in NMR-based screening, researchers often assay mixtures of fragments, rather than single fragments. Herein we present a fast and straightforward computer-aided method to design mixtures of fragments taken from a library that have minimized NMR signal overlap. This approach enables direct identification of one or several active fragments without the need for deconvolution. Our approach entails encoding of NMR spectra into a computer-readable format that we call a fingerprint, and minimizing the global signal overlap through a Monte Carlo algorithm. The scoring function used favors a homogenous distribution of the global signal overlap. The method does not require additional experimental work: the only data required are NMR spectra, which are generally recorded for each compound as a quality control measure before its insertion into the library.

NMRmix: A Tool for the Optimization of Compound Mixtures in 1D 1H NMR Ligand Affinity Screens

“…These statistics are not surprising because the BMRB virtual library consists of mostly small metabolites. Such a high density of aliphatic peaks may reasonably be expected to provide a challenge toward creating mixtures with nonoverlapped peaks; however, a previous analysis indicated that library size and peak distribution do not appear to significantly affect the results of optimization by simulated annealing, 10 and this expectation was confirmed by the results of NMRmix shown below.…”

“…The optimization of mixtures is accomplished by using a simulated annealing algorithm previously described. 10 The user-friendly GUI facilitates easy mixture optimization and data analysis, and NMRmix only requires information about the compound library and a source for reference 1D 1 H peak lists to get started. Additionally, NMRmix introduces the concept of intensity scoring, which penalizes overlaps that occur on the most intense peaks instead of treating overlaps of all peaks equally.…”

“…This last problem can be mitigated by creating mixtures with minimal to no peak overlaps, but the task is onerous and impractical for typical screening libraries composed of hundreds or thousands of compounds. A previous investigation has shown that mixtures with minimal peak overlap could be efficiently created by using a simulated annealing algorithm; 10 however, robust software that implements the algorithm into effective practice is not available.…”

Biophysical Screens Identify Fragments That Bind to the Viral DNA-Binding Proteins EBNA1 and LANA

“…Pooling was performed based on predicted non-overlapping chemical shifts using the NMR prediction algorithms implemented in the Perch software (Perch Solutions). Briefly, a Monte Carlo algorithm was implemented to minimize NMR signal overlap [29]. The threshold for pairwise peak overlap, i.e., minimum distance between non-overlapping peaks, was set at 0.1 ppm.…”

Combined Use of Oligopeptides, Fragment Libraries, and Natural Compounds: A Comprehensive Approach To Sample the Druggability of Vascular Endothelial Growth Factor

“…To speed up the fragment screening, ap reviouslyd escribed computational approach [68] was used to group compounds into cocktails that have minimized NMR signal overlap.T his approach translates the NMR spectra of each compound into ac omputer-readablef ormat (fingerprint) and then minimizes the globals ignal overlap by aS A( Monte-Carlo-Metropolis) algorithm. Using this algorithm, 81 five-fragmentm ixtures, containingatotal of 402 compounds,w erep repared.…”