A. V. Kozintsev

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Sequencing of the human genome along with developments in combinatorial synthesis and high-throughput biological screening provide unparallel opportunities to drug discovery. It has been noted that the increased number of synthesized and annotated compounds did not yield the expected increase in number of viable drug candidates. To address this problem,(More)
We present a novel method to estimate the contributions of translational and rotational entropy to protein-ligand binding affinity. The method is based on estimates of the configurational integral through the sizes of clusters obtained from multiple docking positions. Cluster sizes are defined as the intervals of variation of center of ligand mass and Euler(More)
We present a variational method to derive knowledge-based potentials. The method is based on an optimization procedure of objective variables: atom types, reference states, and interaction cutoff radii. We suggest and apply new unsymmetrical reference states. The cutoff radii and atom types are optimized to improve docking accuracy of the corresponding(More)
We present two novel methods to predict native protein-ligand binding positions. Both methods identify the native binding position as the most probable position corresponding to a maximum of a probability distribution function (PDF) of possible binding positions in a protein active site. Possible binding positions are the origins of clusters composed, on(More)
The variational approach of evaluation for knowledge-based potentials is considered for the first time. In this approach, the problem to derive knowledge-based potentials is solved as the optimization task in the multiparametric model of atom types, reference states and interaction cutoff radii. Using analogy to liquid state theory we offered four new(More)
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