Charge sensitivity approach to mutual polarization of reactants : molecular mechanics perspective

Charge sensitivity analysis (CSA) in force-field atoms resolution was applied to describe the mutual polarization of reactants as well as charge-transfer (CT) effects. An inclusion complex of β-cyclodextrin with salicylic acid was used as a model system. Three CSA models were taken into account and verified on a Born – Oppenheimer molecular dynamics (BOMD) trajectory. The models differed in terms of the equilibrium conditions imposed on the system. It was demonstrated that mutual polarization is an important source of stabilization, in contrast to the results obtained from static charge calculations. The energy lowering induced by CT was small and comparable to the CT stabilization that occurs in hydrogen-bonded systems. All models correctly described the main topological features of the BOMD energy surface. CSA in force-field atoms resolution qualitatively reproduced the charge reorganization accompanying hydrogen-bond formation. It was shown that CSA parameters are very sensitive to the bond formation process, which suggests that they could be applied in reactive force fields as detectors of newly formed chemical bonds

Force Field Analysis Software and Tools (FFAST): Assessing Machine Learning Force Fields Under the Microscope

As the sophistication of Machine Learning Force Fields (MLFF) increases to match the complexity of extended molecules and materials, so does the need for tools to properly analyze and assess the practical performance of MLFFs. To go beyond average error metrics and into a complete picture of a model's applicability and limitations, we develop FFAST (Force Field Analysis Software and Tools): a cross-platform software package designed to gain detailed insights into a model's performance and limitations, complete with an easy-to-use graphical user interface. The software allows the user to gauge the performance of many popular state-of-the-art MLFF models on various popular dataset types, providing general prediction error overviews, outlier detection mechanisms, atom-projected errors, and more. It has a 3D visualizer to find and picture problematic configurations, atoms, or clusters in a large dataset. In this paper, the example of the MACE and Nequip models are used on two datasets of interest -- stachyose and docosahexaenoic acid (DHA) -- to illustrate the use cases of the software. With it, it was found that carbons and oxygens involved in or near glycosidic bonds inside the stachyose molecule present increased prediction errors. In addition, prediction errors on DHA rise as the molecule folds, especially for the carboxylic group at the edge of the molecule. We emphasize the need for a systematic assessment of MLFF models for ensuring their successful application to study the dynamics of molecules and materials.Comment: 22 pages, 11 figure

Pharmacophore derivation using discotech and comparison of semi-emperical, AB initio and density functional CoMFA studies for sigma 1 and sigma 2 receptor-ligands

This study describes the development of pharmacophore and CoMFA models for sigma receptor ligands. CoMFA studies were performed for 48 bioactive sigma 1 receptorligands using [H3 ](+) pentazocine as the radioligand, for 30 PCP derivatives for sigma 1 receptor-ligands using [3H](+)SK-F 10047 as the radioligand and for 24 bioactive sigma 2 receptor-ligands using the radioligand [H3](+)DTG in the presence of pentazocine. Distance Comparisons (DISCOtech) was used as the starting point for CoMFA studies. The conformers, derived by DISCOtech were optimized using AMi, or HF/3-21G* in Gaussian 98. The optimized geometries were aligned with the pharmacophore, derived using DISCOtech. Atomic charges were calculated using AMl, HF/3-21G*, B3LYP/3-21G*, MP2/3-21G* methods in Gaussian 98. The CoMFA Maps that were developed using Sybyl 6.9 were compared on steric and electrostatic field differences. With leaveone-out cross validation the numbers of optimal components were decided. Using these numbers of optimal components no cross validation was performed in a training set. After a test set, it was known that CoMFA models derived from HF/3-21G* optimized geometries were more reliable in predicting bioactivities than CoMFA models derived from AMi optimized geometries

Automated in Silico Design of Homogeneous Catalysts

Catalyst discovery is increasingly relying on computational chemistry, and many of the computational tools are currently being automated. The state of this automation and the degree to which it may contribute to speeding up development of catalysts are the subject of this Perspective. We also consider the main challenges associated with automated catalyst design, in particular the generation of promising and chemically realistic candidates, the tradeoff between accuracy and cost in estimating the catalytic performance, the opportunities associated with automated generation and use of large amounts of data, and even how to define the objectives of catalyst design. Throughout the Perspective, we take a cross-disciplinary approach and evaluate the potential of methods and experiences from fields other than homogeneous catalysis. Finally, we provide an overview of software packages available for automated in silico design of homogeneous catalysts.publishedVersio

Understanding and design of molecular dynamics based simulation methods.

Several new strategies for employing modified molecular dynamics (MD) protocols for finding energy minima were developed developed. First, we derived a new method of searching for the lowest energy conformation by employ employing the results of our work to explain "mean mean-field" molecular dynamics simulation methods. Called ensembles extracted by atomic coordinate transformations (EXACT), the method allows simulations to be performed with a variable degree of approximation. Then, we examine the previously published locally enhanced sampling (LES) approximation. The method makes copies of a small part of interest in a larger system, and allows the dynamics to unfold. The method works by making the copies invisible to each other and allowing them to interact only with the remainder of the system, called the bath. The bath, on the other hand, interacts with an averaged representation of the copied part. This averaged interaction allows the copied particles to move into geometries they might not visit in a conventional MD simulation, which allows a greater variety of structures to be sampled. We derive the algorithm by copying the entire system, and then by employing holonomic constraints between the bath particles between the various systems. Using this new approach, we explore several issues previously noted in the literature. We also use the EXACT approximation method to illustrate the nature of the LES approximation. Finally, we present another optimization method, which add adds pressure along with temperature in analogue with simulated annealing. The method is tested against simulated annealing for condensed phase systems of argon, monoglyme, and tetraglyme. The method noticeably improves the results for the glyme systems, but does not seem to hurt the results for the argon system

A Physics-Based Intermolecular Potential for Biomolecular Simulation

The grand challenge of biophysics is to use the fundamental laws of physics to predict how biological molecules will move and interact. The atomistic HIPPO (Hydrogen-like Intermolecular Polarizable Potential) force field is meant to address this challenge. It does so by breaking down the intermolecular potential energy function of biomolecular interactions into physically meaningful components (electrostatics, polarization, dispersion, and exchangerepulsion) and using this function to drive molecular dynamics simulations. This force field is able to achieve accuracy within 1 kcal/mol for each component when compared with ab initio Symmetry Adapted Perturbation Theory calculations. HIPPO is capable of this accuracy because it introduces a model electron density on every atom in the molecular system. Since the model is built on first-principles physics, it is transferable from small model systems to bulk phase. In the first test case, the HIPPO force field for water was able to reproduce the experimental density, heat of vaporization and dielectric constant to within 1%. Importantly, HIPPO has been shown to be only 10% more computationally expensive than the widely-used AMOEBA force field, meaning that more accurate simulations of larger biological molecules are well within reach

Quantum mechanical bespoke force fields for computer-aided drug design

PhD ThesisThe ability to accurately model complex biological processes such as protein-ligand binding with an atomistic level of detail is critical to their thorough understanding. Typically a molecular mechanics simulation is used, which represents the system using a force eld that is a physically motivated linear combination of empirically parameterised potentials. Traditionally their parameterisation has involved the recreation of experimental and quantum mechanical data for a target set of representative structures, ranging from small molecules to peptides. This potentially limits the progress of general transferable force elds to time and labour-intensive incremental improvements. In this thesis, we aim to challenge this \parameterise once and transfer" philosophy, with that of a transferable parametrisation methodology that can be readily applied to new systems with a consistent level of accuracy. We collect together recently developed force eld parameterisation techniques from the literature to develop a protocol suitable to derive virtually all required force eld parameters for small molecules directly from quantum mechanics. This protocol forms the basis of the QUantum mechanical BEspoke force eld (QUBE) and is delivered to users through a reliable and extensible software toolkit named QUBEKit. Here we extensively benchmark the methodology and software presented through typical force eld performance metrics which involve the prediction of thermodynamical properties of small organic molecules. In this regard, we achieve very competitive accuracy with popular general transferable force elds such as OPLS which have been extensively optimised to reproduce such properties. We also demonstrate how the QUBE force eld is a suitable alternative in a computer-aided drug design setting via the retrospective calculation of the relative binding free energies of 17 inhibitors of p38 MAP kinase. Again good agreement with both experiment and transferable force elds is achieved despite this being the rst generation of the force eld. The results of this work are then particularly important to those studying systems which are not covered or inaccurately represented by standard transferable force elds, as we present an accurate framework towards their complete parameterisation

Application of Computer-Aided Drug Discovery Methodologies Towards the Rational Design of Drugs Against Infectious Diseases

Computer-aided drug discovery involves the application of computer science and programming to solve chemical and biological problems. Specifically, the QSAR (Quantitative Structure Activity Relationships) methodology is used in drug development to provide a rational basis of drug synthesis, rather than a trial and error approach. Molecular dynamics (MD) studies focus on investigating the details of drug-target interactions to elucidate various biophysical characteristics of interest. Infectious diseases like Trypanosoma brucei rhodesiense (TBR) and P. falciparum (malaria) are responsible for millions of deaths annually around the globe. This necessitates an immediate need to design and develop new drugs that efficiently battle these diseases. As a part of the initiatives to improve drug efficacy QSAR studies accomplished the formulation of chemical hypothesis to assist development of drugs against TBR. Results show that CoMSIA 3D QSAR models, with a Pearson’s correlation coefficient of 0.95, predict a compound with meta nitrogens on the phenyl groups, in the combinatorial space based on a biphenyl-furan diamidine design template, to have higher activity against TBR relative to the existing compound set within the same space. Molecular dynamics study, conducted on a linear benzimidazole-biphenyl diamidine that has non-classical structural similarity to earlier known paradigms of minor groove binders, gave insights into the unique water mediated interactions between the DNA minor groove and this ligand. Earlier experiments suggested the interfacial water molecules near the terminal ends of the ligand to be responsible for the exceptianlly high binding constant of the ligand. Results from MD studies show two other modes of binding. The first conformation has a single water molecule with a residency time of 6ns (average) that is closer to the central part of the ligand, which stabilizes the structure in addition to the terminal water. The second conformation that was detected had the ligand completely away from the floor of the minor groove, and hydrogen bonded to the sugar oxygens

From high temperature supercondutivity to quantum spin liquid: progress in strong correlation physics

This review gives a rather general discussion of high temperature superconductors as an example of a strongly correlated material. The argument is made that in view of the many examples of unconventional superconductors discovered in the past twenty years, we should no longer be surprised that superconductivity emerges as a highly competitive ground state in systems where Coulomb repulsion plays a dominant role. The physics of the cuprates is discussed, emphasizing the unusual pseudogap phase in the underdoped region. It is argued that the resonating valence bond (RVB) picture, as formulated using gauge theory with fermionic and bosonic matter fields, gives an adequate physical understanding, even though many details are beyond the powers of current calculational tools. The recent discovery of quantum oscillations in a high magnetic field is discussed in this context. Meanwhile, the problem of the quantum spin liquid (a spin system with antiferromagnetic coupling which refuses to order even at zero temperature) is a somewhat simpler version of the high $T_c$ problem where significant progress has been made recently. It is understood that the existence of matter fields can lead to de-confinement of the U(1) gauge theory in 2+1 dimensions, and novel new particles (called fractionalized particles), such as fermionic spinons which carry spin ${1\over 2}$ and no charge, and gapless gauge bosons can emerge to create a new critical state at low energies. We even have a couple of real materials where such a scenario may be realized experimentally. The article ends with answers to questions such as: what limits $T_c$ if pairing is driven by an electronic energy scale? why is the high $T_c$ problem hard? why is there no consensus? and why is the high $T_c$ problem important?Comment: Submitted as "Key Issue" essay for Report of Progress in Physics; v2: References are added and typos correcte