Eric J. Martin

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The necessity to generate conformations that sample the entire conformational space accessible to a given molecule is ubiquitous in the field of computer-aided drug design. Protein-ligand docking, 3D database searching, and 3D QSAR are three commonly used techniques that depend critically upon the quality and diversity of the generated conformers. Although(More)
Profile-QSAR is a novel 2D predictive model building method for kinases. This "meta-QSAR" method models the activity of each compound against a new kinase target as a linear combination of its predicted activities against a large panel of 92 previously studied kinases comprised from 115 assays. Profile-QSAR starts with a sparse incomplete kinase by compound(More)
Reliable in silico prediction methods promise many advantages over experimental high-throughput screening (HTS): vastly lower time and cost, affinity magnitude estimates, no requirement for a physical sample, and a knowledge-driven exploration of chemical space. For the specific case of kinases, given several hundred experimental IC(50) training(More)
From the perspective of 2D chemical descriptors, error in docking activity predictions is separated into noise and systematic components. This error framework explains how fitting docking scores to a 2D-QSAR equation often improves accuracy as well as its logical limits. Intriguingly, in examined cases where multiple docking models (e.g., multiple crystal(More)
It has been notoriously difficult to develop general all-purpose scoring functions for high-throughput docking that correlate with measured binding affinity. As a practical alternative, AutoShim uses the program Magnet to add point-pharmacophore like "shims" to the binding site of each protein target. The pharmacophore shims are weighted by partial(More)
The "Cheminformatics aspects of high throughput screening (HTS): from robots to models" symposium was part of the computers in chemistry technical program at the American Chemical Society National Meeting in Denver, Colorado during the fall of 2011. This symposium brought together researchers from high throughput screening centers and molecular modelers(More)
Communication of data and ideas within a medicinal chemistry project on a global as well as local level is a crucial aspect in the drug design cycle. Over a time frame of eight years, we built and optimized FOCUS, a platform to produce, visualize, and share information on various aspects of a drug discovery project such as cheminformatics, data analysis,(More)
The 2D Profile-QSAR and 3D Surrogate AutoShim protein-family virtual screening methods were originally developed for kinases. They are the key components of an iterative medium-throughput screening alternative to expensive and time-consuming experimental high-throughput screening. Encouraged by the success with kinases, the S1-serine proteases were selected(More)