Automatic code generation for quantum chemistry applications

A unified, computer algebra system‐based scheme of code‐generation for computational quantum‐chemistry programs is presented. Generation of electron‐repulsion integrals and their derivatives as well as exchange‐correlation potential and its derivatives is discussed. Application to general‐purpose computing on graphics processing units is considered.     

ORBKIT: A modular python toolbox for cross‐platform postprocessing of quantum chemical wavefunction data

ORBKIT is a toolbox for postprocessing electronic structure calculations based on a highly modular and portable Python architecture. The program allows computing a multitude of electronic properties of molecular systems on arbitrary spatial grids from the basis set representation of its electronic wavefunction, as well as several grid‐independent properties. The required data can be extracted directly from the standard output of a large number of quantum chemistry programs. ORBKIT can be used as a standalone program to determine standard quantities, for example, the electron density, molecular orbitals, and derivatives thereof. The cornerstone of ORBKIT is its modular structure. The existing basic functions can be arranged in an individual way and can be easily extended by user‐written modules to determine any other derived quantity. ORBKIT offers multiple output formats that can be processed by common visualization tools (VMD, Molden, etc.). Additionally, ORBKIT possesses routines to order molecular orbitals computed at different nuclear configurations according to their electronic character and to interpolate the wavefunction between these configurations. The program is open‐source under GNU‐LGPLv3 license and freely available at https://github.com/orbkit/orbkit/ . This article provides an overview of ORBKIT with particular focus on its capabilities and applicability, and includes several example calculations. © 2016 Wiley Periodicals, Inc.     

Kinetic barriers in the isomerization of substituted ureas: implications for computer-aided drug design

Urea derivatives are ubiquitously found in many chemical disciplines. N,N′-substituted ureas may show different conformational preferences depending on their substitution pattern. The high energetic barrier for isomerization of the cis and trans state poses additional challenges on computational simulation techniques aiming at a reproduction of the biological properties of urea derivatives. Herein, we investigate energetics of urea conformations and their interconversion using a broad spectrum of methodologies ranging from data mining, via quantum chemistry to molecular dynamics simulation and free energy calculations. We find that the inversion of urea conformations is inherently slow and beyond the time scale of typical simulation protocols. Therefore, extra care needs to be taken by computational chemists to work with appropriate model systems. We find that both knowledge-driven approaches as well as physics-based methods may guide molecular modelers towards accurate starting structures for expensive calculations to ensure that conformations of urea derivatives are modeled as adequately as possible.     

Symmetrizer: Algorithmic determination of point groups in nearly symmetric molecules

Symmetry is an extremely useful and powerful tool in computational chemistry, both for predicting the properties of molecules and for simplifying calculations. Although methods for determining the point groups of perfectly symmetric molecules are well‐known, finding the closest point group for a “nearly” symmetric molecule is far less studied, although it presents many useful applications. For this reason, we introduce Symmetrizer, an algorithm designed to determine a molecule's symmetry elements and closest matching point groups based on a user‐adjustable tolerance, and then to symmetrize that molecule to a given point group geometry. In contrast to conventional methods, Symmetrizer takes a bottom‐up approach to symmetry detection by locating all possible symmetry elements and uses this set to deduce the most probable point groups. We explain this approach in detail, and assess the flexibility, robustness, and efficiency of the algorithm with respect to various input parameters on several test molecules. We also demonstrate an application of Symmetrizer by interfacing it with the WebMO web‐based interface to computational chemistry packages as a showcase of its ease of integration. © 2012 Wiley Periodicals, Inc.     

New rules on potential surface topology and critical point search

The topology of potential energy surfaces provides a unified framework for the study of individual molecular properties, all conformational changes as well as chemical reactions. Molecular behavior, electronic and vibrational properties, conformational freedom, reactivity bond formation and bond breaking are all energy dependent, and the potential energy surface approach provides an elegant, conceptually convenient, although rather complicated representation of this energy dependence. Topology as a mathematical tool is exceptionally suitable for the extraction of the most essential features of complicated representations. By applying topological methods for potential surface analysis, a new, global perspective of many aspects of chemistry emerges. Some of these topological results also have important practical, computational significance. A family of new topological rules and symmetry relations will be adapted for applications in low dimensional relaxed cross-sections of configuration spaces, with a special emphasis on their role in the search for critical points, primarily energy minima and saddle points of transition structures of potential energy surfaces and hypersurfaces.     

Ab initio aqueous thermochemistry: application to the oxidation of hydroxylamine in nitric acid solution

Ab initio molecular orbital calculations were performed and thermochemical parameters estimated for 46 species involved in the oxidation of hydroxylamine in aqueous nitric acid solution. Solution-phase properties were estimated using the several levels of theory in Gaussian03 and using COSMOtherm. The use of computational chemistry calculations for the estimation of physical properties and constants in solution is addressed. The connection between the pseudochemical potential of Ben-Naim and the traditional standard state-based thermochemistry is shown, and the connection of these ideas to computational chemistry results is established. This theoretical framework provides a basis for the practical use of the solution-phase computational chemistry estimates for real systems, without the implicit assumptions that often hide the nuances of solution-phase thermochemistry. The effect of nonidealities and a method to account for them is also discussed. A method is presented for estimating the solvation enthalpy and entropy for dilute aqueous solutions based on the solvation free energy from the ab initio calculations. The accuracy of the estimated thermochemical parameters was determined through comparison with (i) enthalpies of formation in the gas phase and in solution, (ii) Henry's law data for aqueous solutions, and (iii) various reaction equilibria in aqueous solution. Typical mean absolute deviations (MAD) for the solvation free energy in room-temperature water appear to be ~1.5 kcal/mol for most methods investigated. The MAD for computed enthalpies of formation in solution was 1.5-3 kcal/mol, depending on the methodology employed and the type of species (ion, radical, closed-shell) being computed. This work provides a relatively simple and unambiguous approach that can be used to estimate the thermochemical parameters needed to build detailed ab initio kinetic models of systems in aqueous solution. Technical challenges that limit the accuracy of the estimates are highlighted.     

Computational Chemistry to the Rescue: Modern Toolboxes for the Assignment of Complex Molecules by GIAO NMR Calculations

The calculations of NMR properties of molecules using quantum chemical methods have deeply impacted several branches of organic chemistry. They are particularly important in structural or stereochemical assignments of organic compounds, with implications in total synthesis, stereoselective reactions, and natural products chemistry. In studying the evolution of the strategies developed to support (or reject) a structural proposal, it becomes clear that the most effective and accurate ones involve sophisticated procedures to correlate experimental and computational data. Owing to their relatively high mathematical complexity, such calculations (CP3, DP4, ANN‐PRA) are often carried out using additional computational resources provided by the authors (such as applets or Excel files). This Minireview will cover the state‐of‐the‐art of these toolboxes in the assignment of organic molecules, including mathematical definitions, updates, and discussion of relevant examples.     

A versatile AMBER-Gaussian QM/MM interface through PUPIL

The PUPIL package (Program for User Package Interfacing and Linking) originally was developed to interface different programs for multiscale calculations in materials sciences (Torras et al., J Comput Aided Mater Des 2006, 13, 201; Torras et al., Comput Phys Commun 2007, 177, 265). Here we present an extension of PUPIL to computational chemistry by interfacing two widely used computational chemistry programs: AMBER (molecular dynamics) and Gaussian (quantum chemistry). The benefit is to allow the application of the advanced MD techniques available in AMBER to a hybrid QM/MM system in which the forces and energy on the QM part can be computed by any of the methods available in Gaussian. To illustrate, we present two example applications: A MD calculation of alanine dipeptide in explicit water, and a use of the steered MD capabilities in AMBER to calculate the free energy of reaction for the dissociation of Angeli's salt.     

Advance of computational technology for simulating solvent extraction.

Due to recent significant enhancement of computer performance as well as computational techniques, molecular modeling and molecular simulations using computational chemistry can be achieved at the level of practical applications. Even in solvent extraction, the application of computational chemistry to simulations of extraction processes and the molecular design of high-performance extracting agents have gradually been increasing during the last decade. With combining the quantitative structure-property relationship between the molecule properties calculated by the computational chemistry methods and the thermodynamic properties obtained from experiments, researchers can precisely predict the next-generation of extracting agents and novel extraction processes. In this review, the concept of computational chemistry, such as molecular mechanics, molecular orbitals and molecular dynamics calculations, frequently used in the filed of solvent extraction, are outlined. Our systematic research on the solvent-extraction process utilizing MM, MO and MD calculations is also presented.     

Computer-aided drug design platform using PyMOL

The understanding and optimization of protein-ligand interactions are instrumental to medicinal chemists investigating potential drug candidates. Over the past couple of decades, many powerful standalone tools for computer-aided drug discovery have been developed in academia providing insight into protein-ligand interactions. As programs are developed by various research groups, a consistent user-friendly graphical working environment combining computational techniques such as docking, scoring, molecular dynamics simulations, and free energy calculations is needed. Utilizing PyMOL we have developed such a graphical user interface incorporating individual academic packages designed for protein preparation (AMBER package and Reduce), molecular mechanics applications (AMBER package), and docking and scoring (AutoDock Vina and SLIDE). In addition to amassing several computational tools under one interface, the computational platform also provides a user-friendly combination of different programs. For example, utilizing a molecular dynamics (MD) simulation performed with AMBER as input for ensemble docking with AutoDock Vina. The overarching goal of this work was to provide a computational platform that facilitates medicinal chemists, many who are not experts in computational methodologies, to utilize several common computational techniques germane to drug discovery. Furthermore, our software is open source and is aimed to initiate collaborative efforts among computational researchers to combine other open source computational methods under a single, easily understandable graphical user interface.     

Efficient multipole model and linear scaling of NDDO-based methods

Fast growth of computational costs with that of the system's size is a bottleneck for the applications of traditional methods of quantum chemistry to polyatomic molecular systems. This problem is addressed by the development of linear (or almost linear) scaling methods. In the semiempirical domain, it is typically achieved by a series of approximations to the self-consistent field (SCF) solution. By contrast, we propose a route to linear scalability by modifying the trial wave function itself. Our approach is based on variationally determined strictly local one-electron states and a geminal representation of chemical bonds and lone pairs. A serious obstacle previously faced on this route were the numerous transformations of the two-center repulsion integrals characteristic for the neglect of diatomic differential overlap (NDDO) methods. We pass it by replacing the fictitious charge configurations usual for the NDDO scheme by atomic multipoles interacting through semiempirical potentials. It ensures invariance of these integrals and improves the computational efficiency of the whole method. We discuss possible schemes for evaluating the integrals as well as their numerical values. The method proposed is implemented for the most popular modified neglect of diatomic overlap (MNDO), Austin model 1 (AM1), and PM3 parametrization schemes of the NDDO family. Our calculations involving well-justified cutoff procedures for molecular interactions unequivocally show that the proposed scheme provides almost linear scaling of computational costs with the system's size. The numerical results on molecular properties certify that our method is superior with respect to its SCF-based ancestors.     

The Amber biomolecular simulation programs

We describe the development, current features, and some directions for future development of the Amber package of computer programs. This package evolved from a program that was constructed in the late 1970s to do Assisted Model Building with Energy Refinement, and now contains a group of programs embodying a number of powerful tools of modern computational chemistry, focused on molecular dynamics and free energy calculations of proteins, nucleic acids, and carbohydrates.     

Strategic approaches to drug design. I. An integrated software framework for molecular modelling

Summary An integrated molecular graphics and computational chemistry framework is described which has been designed primarily to handle small molecules of up to 300 atoms. The system provides a means of integrating software from any source into a single framework. It is split into two functional subsystems. The first subsystem, called COSMIC. runs on low-cost, serial-linked colour graphics terminals and allows the user to prepare and examine structural data and to submit them for extensive computational chemistry. Links also allow access to databases, other modelling systems and user-written modules. Much of the output from COSMIC cannot be examined with low level graphics. A second subsystem, called ASTRAL, has been developed for the high-resolution Evans & Sutherland PS300 colour graphics terminal and is designed to manipulate complex display structures. The COSMIC minimisers, geometry investigators, molecular orbital displays, electrostatic isopotential generators and various interfaces and utilities are described.     

机器学习在团簇研究中的可能应用

团簇的结构-能量关系非常复杂,存在大量的局部能量极小点,寻找全局稳定结构是个很艰巨的任务。对于中大尺寸团簇的计算,采用纯量子力学计算方法将面临非常重的计算负担,而如果采用传统力场的方法则会面临精度不足的困难。近年来崛起的机器学习浪潮,开始渗透到包括化学在内的各个学科领域。基于机器学习的方法,有可能提供一条介乎量子力学与传统力场之间的中间新路线。发展基于机器学习的团簇势能模型,用于寻找中大尺寸团簇的稳定结构,有望为团簇的理论与计算研究提供新思路与新手段。     

Testing electronic structure methods for describing intermolecular H...H interactions in supramolecular chemistry

In this article a wide variety of computational approaches (molecular mechanics force fields, semiempirical formalisms, and hybrid methods, namely ONIOM calculations) have been used to calculate the energy and geometry of the supramolecular system 2-(2'-hydroxyphenyl)-4-methyloxazole (HPMO) encapsulated in beta-cyclodextrin (beta-CD). The main objective of the present study has been to examine the performance of these computational methods when describing the short range H. H intermolecular interactions between guest (HPMO) and host (beta-CD) molecules. The analyzed molecular mechanics methods do not provide unphysical short H...H contacts, but it is obvious that their applicability to the study of supramolecular systems is rather limited. For the semiempirical methods, MNDO is found to generate more reliable geometries than AM1, PM3 and the two recently developed schemes PDDG/MNDO and PDDG/PM3. MNDO results only give one slightly short H...H distance, whereas the NDDO formalisms with modifications of the Core Repulsion Function (CRF) via Gaussians exhibit a large number of short to very short and unphysical H...H intermolecular distances. In contrast, the PM5 method, which is the successor to PM3, gives very promising results. Our ONIOM calculations indicate that the unphysical optimized geometries from PM3 are retained when this semiempirical method is used as the low level layer in a QM:QM formulation. On the other hand, ab initio methods involving good enough basis sets, at least for the high level layer in a hybrid ONIOM calculation, behave well, but they may be too expensive in practice for most supramolecular chemistry applications. Finally, the performance of the evaluated computational methods has also been tested by evaluating the energetic difference between the two most stable conformations of the host(beta-CD)-guest(HPMO) system.     

Performance of SCAN density functional for a set of ionic liquid ion pairs

Computational chemistry is a powerful tool for the discovery of novel materials. In particular, it is used to simulate ionic liquids in search of electrolytes for electrochemical applications. Herein, the choice of the computational method is not trivial, as it has to be both efficient and accurate. Density functional theory methods with appropriate corrections for the systematic weaknesses can give precision close to that of the post‐Hartree–Fock coupled cluster methods with a fraction of their cost. Thence, we have evaluated the performance of a recently developed nonempirical strongly constrained and appropriately normed (SCAN) density functional on electronic structure calculations of ionic liquid ion pairs. The performance of SCAN and other popular functionals (PBE, M06‐L, B2PLYP) among with Grimme's dispersion correction and Boys–Bernardi basis set superposition error correction was compared to DLPNO‐CCSD(T)/CBS. We show that SCAN reproduces coupled‐cluster results for describing the employed dataset of 48 ion pairs.     

Quantum Mechanics/Molecular Mechanics Modeling of Enzymatic Processes: Caveats and Breakthroughs

Nature has developed large groups of enzymatic catalysts with the aim to transfer substrates into useful products, which enables biosystems to perform all their natural functions. As such, all biochemical processes in our body (we drink, we eat, we breath, we sleep, etc.) are governed by enzymes. One of the problems associated with research on biocatalysts is that they react so fast that details of their reaction mechanisms cannot be obtained with experimental work. In recent years, major advances in computational hardware and software have been made and now large (bio)chemical systems can be studied using accurate computational techniques. One such technique is the quantum mechanics/molecular mechanics (QM/MM) technique, which has gained major momentum in recent years. Unfortunately, it is not a black‐box method that is easily applied, but requires careful set‐up procedures. In this work we give an overview on the technical difficulties and caveats of QM/MM and discuss work‐protocols developed in our groups for running successful QM/MM calculations.