The accurate and exhaustive description of the conformational ensemble sampled by small molecules in solution, possibly at different physiological conditions, is of primary interest in many fields of medicinal chemistry and computational biology. Recently, we have built an on-line database of compounds with antimicrobial properties, where we provide all-atom force-field parameters and a set of molecular properties, including representative structures extracted from cluster analysis over µs-long molecular dynamics (MD) trajectories. In the present work, we used a medium-sized antibiotic from our sample, namely ampicillin, to assess the quality of the conformational ensemble. To this aim, we compared the conformational landscape extracted from previous unbiased MD simulations to those obtained by means of Replica Exchange MD (REMD) and those originating from three freely-available conformer generation tools widely adopted in computer-aided drug-design. In addition, for different charge/protonation states of ampicillin, we made available force-field parameters and static/dynamic properties derived from both Density Functional Theory and MD calculations. For the specific system investigated here, we found that: (i) the conformational statistics extracted from plain MD simulations is consistent with that obtained from REMD simulations; (ii) overall, our MD-based approach performs slightly better than any of the conformer generator tools if one takes into account both the diversity of the generated conformational set and the ability to reproduce experimentally-determined structures

Extracting conformational ensembles of small molecules from molecular dynamics simulations: ampicillin as a test case

MALLOCI, GIULIANO;SERRA, GIOVANNI;BOSIN, ANDREA;VARGIU, ATTILIO VITTORIO
2016-01-01

Abstract

The accurate and exhaustive description of the conformational ensemble sampled by small molecules in solution, possibly at different physiological conditions, is of primary interest in many fields of medicinal chemistry and computational biology. Recently, we have built an on-line database of compounds with antimicrobial properties, where we provide all-atom force-field parameters and a set of molecular properties, including representative structures extracted from cluster analysis over µs-long molecular dynamics (MD) trajectories. In the present work, we used a medium-sized antibiotic from our sample, namely ampicillin, to assess the quality of the conformational ensemble. To this aim, we compared the conformational landscape extracted from previous unbiased MD simulations to those obtained by means of Replica Exchange MD (REMD) and those originating from three freely-available conformer generation tools widely adopted in computer-aided drug-design. In addition, for different charge/protonation states of ampicillin, we made available force-field parameters and static/dynamic properties derived from both Density Functional Theory and MD calculations. For the specific system investigated here, we found that: (i) the conformational statistics extracted from plain MD simulations is consistent with that obtained from REMD simulations; (ii) overall, our MD-based approach performs slightly better than any of the conformer generator tools if one takes into account both the diversity of the generated conformational set and the ability to reproduce experimentally-determined structures
2016
Ampicillin, Molecular databases, Molecular descriptors, All-atom force fields, Molecular dynamics simulations, Computer-aided drug design, Conformer generation tools
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11584/138461
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