Network


Latest external collaboration on country level. Dive into details by clicking on the dots.

Hotspot


Dive into the research topics where Peter I. Maxwell is active.

Publication


Featured researches published by Peter I. Maxwell.


Molecular Physics | 2016

Transferable Atoms: An Intra-Atomic Perspective through the study of Homogeneous Oligopeptides

Peter I. Maxwell; Paul L. A. Popelier

ABSTRACT Quantifying an atoms transferability, in a force field context, demands a quantitative understanding of how an atom ‘experiences’ the surrounding environment both intra-atomically and inter-atomically. Here we investigate the intra-atomic (EintraA) viewpoint through the study of the atoms Cα, Hα, N, O, and S in a series of ‘mono’-, tri- and penta-peptides. The remaining inter-atomic viewpoint consists of an electrostatic (via multipole moments), exchange and correlation components respectively, of which the electrostatic component has been previously reported. Together these four energy components, as calculated from the Interacting Quantum Atoms (IQA) partitioning approach, express the foundation of the Quantum Chemical Topological Force Field (QCTFF). In order to have transferability within a force field, smaller sample systems must be calculated and developed as representative of larger target systems. The Cα, Hα, N, O and S atoms in a tri-peptide are energetically comparable to those in their penta-peptide configurations, within 2.1 kJ/mol in absolute value (1 exception). Across all five elements, this energy difference is on average ∼0.3 kJ/mol. On average, the tri-peptide sample systems represent a ∼8.2 Å atomic horizon around the central atoms of interest. Thus, both the previous knowledge of the ∼10.3 Å horizon sphere and ∼0.4 kJ/mol error required by the electrostatic multipole moments, determine how two of the four key QCTFF energy components are affected by an atoms molecular environment.


Journal of Chemical Information and Modeling | 2016

Hydrogen-Bond Accepting Properties of New Heteroaromatic Ring Chemical Motifs: A Theoretical Study.

Jérôme Graton; Jean-Yves Le Questel; Peter I. Maxwell; Paul L. A. Popelier

UNLABELLED The prediction of hydrogen-bond (H-bond) acceptor ability is crucial in drug design. This important property is quantified in a large pKBHX database of consistently measured values. We aim to expand the chemical diversity of the studied H-bond acceptors and to increase the range of H-bond strength considered. Two quantum chemical descriptors are contrasted, called ΔE(H) (the change in the energy of a topological hydrogen atom upon complexation) and Vmin (the local minimum in the electrostatic potential on the H-bond accepting site). We performed a systematic analysis of the correlations between pKBHX and Vmin for an initial set of 106 compounds (including O- and N-containing subsets, as well as compounds including sulfur, chlorine, and π-bases). Correlations improve for family dependent subsets, and after outlier treatment, a set of 90 compounds was used to set up a linear equation to predict pKBHX from Vmin. This equation and a previously published equation [Green and Popelier J. Chem. Inf. MODEL 2014, 54 (2), 553-561], to predict pKBHX from ΔE(H), were used to predict the pKBHX values for 22 potentially biologically active heteroaromatic ring compounds, [Pitt et al. J. Med. Chem. 2009, 52 (9), 2952-2963], among which several structures still remain experimentally unavailable. H-Bond basicity of sp(2) nitrogen sites were consistently predicted with both descriptors. A worse agreement was found with carbonyl acceptor sites, with the stronger deviations observed for the lactam groups. It was shown that secondary interactions involving the neighboring NH group were influencing the results. Substitution of the NH group with an NMe group resulted in an improved consistency from both Vmin and ΔE(H) predictions, the latter being more prominently affected by the methyl substitution. Both approaches appear as efficient procedures for the H-bond ability prediction of novel heteroaromatic rings. Nevertheless, the ΔE(H) parameter presents slight chemical structure limitations and requires more detailed H-bond structure investigations.


Journal of Computational Chemistry | 2017

Unfavorable regions in the ramachandran plot: Is it really steric hindrance? The interacting quantum atoms perspective

Peter I. Maxwell; Paul L. A. Popelier

Accurate description of the intrinsic preferences of amino acids is important to consider when developing a biomolecular force field. In this study, we use a modern energy partitioning approach called Interacting Quantum Atoms to inspect the cause of the φ and ψ torsional preferences of three dipeptides (Gly, Val, and Ile). Repeating energy trends at each of the molecular, functional group, and atomic levels are observed across both (1) the three amino acids and (2) the φ/ψ scans in Ramachandran plots. At the molecular level, it is surprisingly electrostatic destabilization that causes the high‐energy regions in the Ramachandran plot, not molecular steric hindrance (related to the intra‐atomic energy). At the functional group and atomic levels, the importance of key peptide atoms (Oi–1, Ci, Ni, Ni+1) and some sidechain hydrogen atoms (Hγ) are identified as responsible for the destabilization seen in the energetically disfavored Ramachandran regions. Consistently, the Oi–1 atoms are particularly important for the explanation of dipeptide intrinsic behavior, where electrostatic and steric destabilization unusually complement one another. The findings suggest that, at least for these dipeptides, it is the peptide group atoms that dominate the intrinsic behavior, more so than the sidechain atoms.


Molecular Simulation | 2018

Towards the simulation of biomolecules: optimisation of peptide-capped glycine using FFLUX

Joseph C. R. Thacker; Alex L. Wilson; Zak E. Hughes; Matthew J. Burn; Peter I. Maxwell; Paul L. A. Popelier

Abstract The optimisation of a peptide-capped glycine using the novel force field FFLUX is presented. FFLUX is a force field based on the machine-learning method kriging and the topological energy partitioning method called Interacting Quantum Atoms. FFLUX has a completely different architecture to that of traditional force fields, avoiding (harmonic) potentials for bonded, valence and torsion angles. In this study, FFLUX performs an optimisation on a glycine molecule and successfully recovers the target density-functional-theory energy with an error of 0.89 ± 0.03 kJ mol−1. It also recovers the structure of the global minimum with a root-mean-squared deviation of 0.05 Å (excluding hydrogen atoms). We also show that the geometry of the intra-molecular hydrogen bond in glycine is recovered accurately.


Physical Chemistry Chemical Physics | 2016

Extension of the interacting quantum atoms (IQA) approach to B3LYP level density functional theory (DFT)

Peter I. Maxwell; Ángel Martín Pendás; Paul L. A. Popelier


Theoretical Chemistry Accounts | 2016

The prediction of topologically partitioned intra‑atomic and inter‑atomic energies by the machine learning method kriging

Peter I. Maxwell; Nicodemo Di Pasquale; Salvatore Cardamone; Paul L. A. Popelier


Physical Chemistry Chemical Physics | 2017

The long-range convergence of the energetic properties of the water monomer in bulk water at room temperature

Stuart J. Davie; Peter I. Maxwell; Paul L. A. Popelier


Structural Chemistry | 2017

Accurate prediction of the energetics of weakly bound complexes using the machine learning method kriging

Peter I. Maxwell; Paul L. A. Popelier


Scientific Reports | 2017

Geometry Optimization with Machine Trained Topological Atoms

François Zielinski; Peter I. Maxwell; Timothy L. Fletcher; Stuart J. Davie; Nicodemo Di Pasquale; Salvatore Cardamone; Matthew J. L. Mills; Paul L. A. Popelier


Theoretical Chemistry Group Graduate Student Meeting | 2015

Transferable Atoms: The Topological Energy Partitioning (TEP) Perspective

Peter I. Maxwell; Stuart J. Davie; Paul L. A. Popelier

Collaboration


Dive into the Peter I. Maxwell's collaboration.

Top Co-Authors

Avatar
Top Co-Authors

Avatar
Top Co-Authors

Avatar
Top Co-Authors

Avatar
Top Co-Authors

Avatar

Alex L. Wilson

University of Manchester

View shared research outputs
Top Co-Authors

Avatar
Top Co-Authors

Avatar
Top Co-Authors

Avatar
Top Co-Authors

Avatar
Top Co-Authors

Avatar
Researchain Logo
Decentralizing Knowledge