Literature DB >> 28682617

Conformation Generation: The State of the Art.

Paul C D Hawkins1.   

Abstract

The generation of conformations for small molecules is a problem of continuing interest in cheminformatics and computational drug discovery. This review will present an overview of methods used to sample conformational space, focusing on those methods designed for organic molecules commonly of interest in drug discovery. Different approaches to both the sampling of conformational space and the scoring of conformational stability will be compared and contrasted, with an emphasis on those methods suitable for conformer sampling of large numbers of drug-like molecules. Particular attention will be devoted to the appropriate utilization of information from experimental solid-state structures in validating and evaluating the performance of these tools. The review will conclude with some areas worthy of further investigation.

Keywords:  Conformations; Conformers; Molecular energetics; Sampling; Stochastic; Structural information; Systematic; Validation

Mesh:

Year:  2017        PMID: 28682617     DOI: 10.1021/acs.jcim.7b00221

Source DB:  PubMed          Journal:  J Chem Inf Model        ISSN: 1549-9596            Impact factor:   4.956


  27 in total

1.  Improving ligand 3D shape similarity-based pose prediction with a continuum solvent model.

Authors:  Ashutosh Kumar; Kam Y J Zhang
Journal:  J Comput Aided Mol Des       Date:  2019-08-28       Impact factor: 3.686

2.  Computational Approach to Molecular Catalysis by 3d Transition Metals: Challenges and Opportunities.

Authors:  Konstantinos D Vogiatzis; Mikhail V Polynski; Justin K Kirkland; Jacob Townsend; Ali Hashemi; Chong Liu; Evgeny A Pidko
Journal:  Chem Rev       Date:  2018-10-30       Impact factor: 60.622

3.  Conformational ensemble comparison for small molecules in drug discovery.

Authors:  Matthew Habgood
Journal:  J Comput Aided Mol Des       Date:  2018-07-09       Impact factor: 3.686

4.  Shape similarity guided pose prediction: lessons from D3R Grand Challenge 3.

Authors:  Ashutosh Kumar; Kam Y J Zhang
Journal:  J Comput Aided Mol Des       Date:  2018-08-06       Impact factor: 3.686

5.  Predicting Molecular Energy Using Force-Field Optimized Geometries and Atomic Vector Representations Learned from an Improved Deep Tensor Neural Network.

Authors:  Jianing Lu; Cheng Wang; Yingkai Zhang
Journal:  J Chem Theory Comput       Date:  2019-06-12       Impact factor: 6.006

6.  A Variable Neighbourhood Descent Heuristic for Conformational Search Using a Quantum Annealer.

Authors:  D J J Marchand; M Noori; A Roberts; G Rosenberg; B Woods; U Yildiz; M Coons; D Devore; P Margl
Journal:  Sci Rep       Date:  2019-09-23       Impact factor: 4.379

7.  ReSCoSS: a flexible quantum chemistry workflow identifying relevant solution conformers of drug-like molecules.

Authors:  Anikó Udvarhelyi; Stephane Rodde; Rainer Wilcken
Journal:  J Comput Aided Mol Des       Date:  2020-08-17       Impact factor: 3.686

Review 8.  Towards operando computational modeling in heterogeneous catalysis.

Authors:  Lukáš Grajciar; Christopher J Heard; Anton A Bondarenko; Mikhail V Polynski; Jittima Meeprasert; Evgeny A Pidko; Petr Nachtigall
Journal:  Chem Soc Rev       Date:  2018-11-12       Impact factor: 54.564

9.  Dataset Construction to Explore Chemical Space with 3D Geometry and Deep Learning.

Authors:  Jianing Lu; Song Xia; Jieyu Lu; Yingkai Zhang
Journal:  J Chem Inf Model       Date:  2021-03-08       Impact factor: 4.956

10.  Prediction of n-octanol/water partition coefficients and acidity constants (pKa) in the SAMPL7 blind challenge with the IEFPCM-MST model.

Authors:  Antonio Viayna; Silvana Pinheiro; Carles Curutchet; F Javier Luque; William J Zamora
Journal:  J Comput Aided Mol Des       Date:  2021-07-10       Impact factor: 3.686

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