AM1/d-CB1: A Semiempirical Model for QM/MM Simulations of Chemical Glycobiology Systems

Identification of a Common Pharmacophore for Binding to MMP2 and RGD Integrin: Towards a Multitarget Approach to Inhibit Cancer Angiogenesis and Metastasis

During tumor angiogenesis different growth factors, cytokines and other molecules interact closely with each other to facilitate tumor cell invasion and metastatic diffusion. The most intensively studied as molecular targets in anti-angiogenic therapies are vascular endothelial growth factor (VEGF) and related receptors, integrin receptors and matrix metalloproteinases (MMPs). Considering the poor efficacy of cancer angiogenesis monotherapies, we reasoned combining the inhibition of αvβ3 and MMP2 as a multitarget approach to deliver a synergistic blockade of tumor cell migration, invasion and metastasis. Accordingly, we identified a common pharmacophore in the binding cavity of MMP2 and αvβ3, demonstrating such approach with the design, synthesis and bioassays of tyrosine-derived peptidomimetics carrying the necessary functional groups to bind to key pharmacophoric elements of MMP2 and αvβ3 RGD integrin.

Multidimensional Free Energy and Accelerated Quantum Library Methods Provide a Gateway to Glycoenzyme Conformational, Electronic, and Reaction Mechanisms

Enzyme reactions are complex to simulate accurately, and none more so than glycoenzymes (glycosyltransferase and glycosidases). A rigorous sampling of the protein frame and the conformationally plural carbohydrate substrate coupled with an unbiased treatment of the electron dynamics is needed to discover the true reaction landscapes. Here, we demonstrate the effectiveness of two computational methods ported in libraries that we have developed. The first is a flat histogram free energy method called FEARCF capable of multidimensional sampling and rapidly converging to a complete coverage of phase space. The second, the Quantum Supercharger Library (QSL), is a method that accelerates the computation of the ab initio electronic wave function as well as the integral derivatives on graphical processing units (GPUs). These QSL accelerated computations form the core components needed for direct quantum dynamics and QM/MM dynamics when coupled with legacy codes such as GAMESS and NWCHEM, making state of the art hyper-parallel electronic computations in chemistry and chemical biology possible. The combination of QSL (acceleration of ab initio QM computation) and FEARCF (multidimensional hyper-parallel reaction dynamics) makes the simulation of ab initio QM/MM reaction dynamics of enzyme catalysis feasible. Enzymes that process carbohydrates pose an added challenge as their pyranose ring substrates span multidimensional conformational space whose sampling is an intimate function of the catalytic mechanism. Here, we use the pairing of FEARCF and QSL to simulate the catalytic effect of the glycoenzyme β-N-acetylglucosamine transferase (OGT). The reaction mechanism is discovered from a variable three bond reaction surface using SCCDFTB. The role of the OGT in distorting the pyranose ring of β-N-acetylglucosamine (GlcNAc) away from the equilibrium 4C1 chair conformation toward the E3 envelope needed for the transition state is discovered from its pucker free energy hypersurfaces (or free energy volume, FEV). A complete GlcNAc ring pucker HF 6-31g FEV is constructed from ab initio QM dynamics in vacuum and ab initio QM/MM dynamics in the OGT catalytic domain. The OGT is shown to clearly lower the pathway toward the transition state E3 ring conformer as well as stabilize it by 1.63 kcal/mol. Illustrated here is the use of QSL accelerated ab initio QM/MM dynamics that thoroughly explores carbohydrate catalyzed reactions through a FEARCF multidimensional sampling of the interdependence between reaction and conformational space. This demonstrates how experimentally inaccessible molecular and electronic mechanisms that underpin enzyme catalysis can be discovered by directly modeling the dynamics of these complex reactions.

Development and application of quantum mechanics/molecular mechanics methods with advanced polarizable potentials

Quantum mechanics/molecular mechanics (QM/MM) simulations are a popular approach to study various features of large systems. A common application of QM/MM calculations is in the investigation of reaction mechanisms in condensed-phase and biological systems. The combination of QM and MM methods to represent a system gives rise to several challenges that need to be addressed. The increase in computational speed has allowed the expanded use of more complicated and accurate methods for both QM and MM simulations. Here, we review some approaches that address several common challenges encountered in QM/MM simulations with advanced polarizable potentials, from methods to account for boundary across covalent bonds and long-range effects, to polarization and advanced embedding potentials.

Three-Dimensional Structures of Carbohydrates and Where to Find Them

Analysis and systematization of accumulated data on carbohydrate structural diversity is a subject of great interest for structural glycobiology. Despite being a challenging task, development of computational methods for efficient treatment and management of spatial (3D) structural features of carbohydrates breaks new ground in modern glycoscience. This review is dedicated to approaches of chemo- and glyco-informatics towards 3D structural data generation, deposition and processing in regard to carbohydrates and their derivatives. Databases, molecular modeling and experimental data validation services, and structure visualization facilities developed for last five years are reviewed.

Computational Drug Designing and Prediction Of Important Parameters Using in silico Methods- A Review

BACKGROUND

Computational or in silico studies are undertaken to assess the drug like properties of lead compounds. These studies help in fast prediction of relevant properties.

OBJECTIVE

Through this review, an effort is made to encapsulate some of the important parameters which should be met by a compound for it to be considered as a potential drug candidate along with an overview of automated softwares which can be used for making various predictions.

METHODS

Drug uptake, its absorption, evacuation and associated hazardous effects are important factors for consideration in drug designing and should be known in early stages of drug development. Several important physicochemical properties like molecular weight, polar surface area (PSA), molecular flexibility etc. have to be taken into consideration in drug designing. Toxicological assessment is another important aspect of drug discovery which predicts the safety and adverse effects of a drug.

RESULTS

Additionally, bioactivity scores of probable drug leads against various human receptors can also be predicted to evaluate the probability of them to act as a potential drug candidate. The in vivo biological targets of a molecule can also be efficiently predicted by molecular docking studies.

CONCLUSION

Some important software like iGEMDOCK, AutoDock, OSIRIS property explorer, Molinspiration, MetaPrint2D, admetSAR and their working methodology and principle of working have been summarized in this review.

Combination of multicomponent KA2 and Pauson-Khand reactions: short synthesis of spirocyclic pyrrolocyclopentenones

The Cu-catalyzed multicomponent ketone–amine–alkyne (KA²) reaction was combined with a Pauson–Khand cycloaddition to give access of unprecedented constrained spirocyclic pyrrolocyclopentenone derivatives following a DOS couple-pair approach. The polyfunctional molecular scaffolds were tested on the cyclopentenone reactivity to further expand the skeletal diversity, demonstrating the utility of this combined approach in generating novel spiro compounds as starting material for the generation of chemical libraries. The chemoinformatics characterization of the newly-synthesized molecules gave evidence about structural and physicochemical properties with respect to a set of blockbuster drugs, and showed that such scaffolds are drug-like but more spherical and three-dimensional in character than the drugs.

Semi-Empirical Born-Oppenheimer Molecular Dynamics (SEBOMD) within the Amber Biomolecular Package

Semi-empirical quantum methods from the neglect of differential diatomic overlap (NDDO) family such as MNDO, AM1, or PM3 are fast albeit approximate quantum methods. By combining them with linear scaling methods like the divide & conquer (D&C) method, it is possible to quickly evaluate the energy of systems containing hundreds to thousands of atoms. We here present our implementation in the Amber biomolecular package of a SEBOMD module that provides a way to run semi-empirical Born-Oppenheimer molecular dynamics. At each step of a SEBOMD, a fully converged self-consistent field (SCF) calculation is performed to obtain the semiempirical quantum potential energy of a molecular system encaged or not in periodic boundary conditions. We describe the implementation and the features of our SEBOMD implementation. We show the requirements to conserve the total energy in NVE simulations, and how to accelerate SCF convergence through density matrix extrapolation. Specific ways of handling periodic boundary conditions using mechanical embedding or electrostatic embedding through a tailored quantum Ewald summation is developed. The parallel performance of SEBOMD simulations using the D&C scheme are presented for liquid water systems of various sizes, and a comparison between the traditional full diagonalization scheme and the D&C approach for the reproduction of the structure of liquid water illustrates the potentiality of SEBOMD to simulate molecular systems containing several hundreds of atoms for hundreds of picoseconds with a quantum mechanical potential in a reasonable amount of CPU time.

Molecular dynamics simulations of hexopyranose ring distortion in different force fields

The four classical, biomolecular force fields designed to study hexopyranose-based carbohydrates (GROMOS 56a6CARBO/56a6CARBO_R, GROMOS 53a6GLYC, CHARMM and GLYCAM06) have been tested in the context of ring-inversion properties. These properties were evaluated for both unfunctionalized monomers of all hexopyranoses of the d series and for residues in a chain composed of uniform units connected by α(1→4) and β(1→4) glycosidic linkages. The results indicate that the tested force fields differ in their predictions of the ring-inversion properties of both monomers and residues in a chain. The comparison with the available experimental data and with the semi-empirical Angyal scheme reveals that, at the level of monomers, GROMOS 56a6CARBO, GROMOS 53a6GLYC and CHARMM correctly reproduce the ring-inversion free energies. However, due to the lack of analogous reference data we cannot state which force field is more or less accurate in the context of ring distortion of residues in a chain. Therefore, the use of ab initio potentials is recommended in the prospective, quantitative studies on the related subject.

Producing DFT/MM enzyme reaction trajectories from SCC-DFTB/MM driving forces to probe the underlying electronics of a glycosyltransferase reaction

The SCC-DFTB/MIO/CHARMM free energy surface for a glycosyltransferase, TcTS, is benchmarked against a DFT/MM reaction trajectory using the same CHARMM MM force field ported to the NWChem package. The popular B3LYP functional, against which the MIO parameter set was parameterized is used to optimize TS structures and run DFT reaction dynamics. A novel approach was used to generate reaction forces from a SCC-DFTB/MIO/CHARMM reaction surface to drive B3LYP/6-31G/MM and B3LYP/6-31G(d)/MM reaction trajectories. Although TS structures compare favorably, differences stemming primarily from a minimal basis set approximation prevented a successful 6-31G(d) FEARCF reaction dynamics trajectory. None the less, the dynamic evolution of the B3LYP/6-31G/MM-computed electron density provided an opportunity to perform NBO analysis along the reaction trajectory. Here, we illustrate that a successful ab initio reaction trajectory is computationally accessible when the underlying potential energy function of the semi-empirical method used to produce driving forces is sufficiently close to the ab initio potential. © 2017 Wiley Periodicals, Inc.

Acceleration of Semiempirical QM/MM Methods through Message Passage Interface (MPI), Hybrid MPI/Open Multiprocessing, and Self-Consistent Field Accelerator Implementations

The strategy and implementation of scalable and efficient semiempirical (SE) QM/MM methods in CHARMM are described. The serial version of the code was first profiled to identify routines that required parallelization. Afterward, the code was parallelized and accelerated with three approaches. The first approach was the parallelization of the entire QM/MM routines, including the Fock matrix diagonalization routines, using the CHARMM message passage interface (MPI) machinery. In the second approach, two different self-consistent field (SCF) energy convergence accelerators were implemented using density and Fock matrices as targets for their extrapolations in the SCF procedure. In the third approach, the entire QM/MM and MM energy routines were accelerated by implementing the hybrid MPI/open multiprocessing (OpenMP) model in which both the task- and loop-level parallelization strategies were adopted to balance loads between different OpenMP threads. The present implementation was tested on two solvated enzyme systems (including <100 QM atoms) and an S_N2 symmetric reaction in water. The MPI version exceeded existing SE QM methods in CHARMM, which include the SCC-DFTB and SQUANTUM methods, by at least 4-fold. The use of SCF convergence accelerators further accelerated the code by ∼12-35% depending on the size of the QM region and the number of CPU cores used. Although the MPI version displayed good scalability, the performance was diminished for large numbers of MPI processes due to the overhead associated with MPI communications between nodes. This issue was partially overcome by the hybrid MPI/OpenMP approach which displayed a better scalability for a larger number of CPU cores (up to 64 CPUs in the tested systems).

Pyranose ring conformations in mono- and oligosaccharides: a combined MD and DFT approach

A two-step computational protocol is proposed to efficiently study the conformational properties of hexopyranoses with a special emphasis on their ring-inversion-properties. By applying it, the errors resulting from overestimating the contribution of the hydrogen bond-rich, low-energy structures that are not abundant in aqueous solutions are avoided.

Different QM/MM Approaches To Elucidate Enzymatic Reactions: Case Study on ppGalNAcT2

Hybrid QM/MM computational studies can provide invaluable insight into the mechanisms of enzymatic reactions that can be exploited for rational drug design. Various approaches are available for such studies. However, their strengths and weaknesses may not be immediately apparent. Using the retaining glycosyltransferase ppGalNAcT2 as a case study, we compare different methodologies used to obtain reaction paths and transition state information. Ab Initio MD using CPMD coupled with the String Method is used to derive the minimum free energy reaction path. The geometrical features of the free energy path, especially around the transition state, agree with the minimum potential energy path obtained by the much less computationally expensive Nudged Elastic Band method. The barrier energy, however, differs by 8 kcal/mol. The free energy surface generated by metadynamics provides a rough overview of the reaction and can confirm the physical relevance of optimized paths or provide an initial guess for path optimization methods. Calculations of enzymatic reactions are usually performed at best at the DFT level of theory. A comparison of widely used functionals with high-level DLPNO-CCSD(T)/CBS data on the potential energy profile serves as a validation of the usability of DFT for this type of enzymatic reaction. The M06-2X meta-hybrid functional in particular matches the DLPNO-CCSD(T)/CBS reference extremely well with errors within 1 kcal/mol. However, even pure-GGA functional OPBE provides sufficient accuracy for this type of study.

Improved Sugar Puckering Profiles for Nicotinamide Ribonucleoside for Hybrid QM/MM Simulations

The coenzyme nicotinamide adenine dinucleotide (NAD⁺) and its reduced form (NADH) play ubiquitous roles as oxidizing and reducing agents in nature. The binding, and possibly the chemical redox step, of NAD⁺/NADH may be influenced by the cofactor conformational distribution and, in particular, by the ribose puckering of its nicotinamide-ribonucleoside (NR) moiety. In many hybrid quantum mechanics-molecular mechanics (QM/MM) studies of NAD⁺/NADH dependent enzymes, the QM region is treated by semiempirical (SE) methods. Recent work suggests that SE methods do not adequately describe the ring puckering in sugar molecules. In the present work we adopt an efficient and practical strategy to correct for this deficiency for NAD⁺/NADH. We have implemented a cost-effective correction to a SE Hamiltonian by adding a correction potential, which is defined as the difference between an accurate benchmark density functional theory (DFT) potential energy surface (PES) and the SE PES. In practice, this is implemented via a B-spline interpolation scheme for the grid-based potential energy difference surface. We find that the puckering population distributions obtained from free energy QM(SE)/MM simulations are in good agreement with DFT and in fair accord with experimental results. The corrected PES should facilitate a more accurate description of the ribose puckering in the NAD⁺/NADH cofactor in simulations of biological systems.

Semiempirical Quantum Mechanical Methods for Noncovalent Interactions for Chemical and Biochemical Applications

Semiempirical (SE) methods can be derived from either Hartree-Fock or density functional theory by applying systematic approximations, leading to efficient computational schemes that are several orders of magnitude faster than ab initio calculations. Such numerical efficiency, in combination with modern computational facilities and linear scaling algorithms, allows application of SE methods to very large molecular systems with extensive conformational sampling. To reliably model the structure, dynamics, and reactivity of biological and other soft matter systems, however, good accuracy for the description of noncovalent interactions is required. In this review, we analyze popular SE approaches in terms of their ability to model noncovalent interactions, especially in the context of describing biomolecules, water solution, and organic materials. We discuss the most significant errors and proposed correction schemes, and we review their performance using standard test sets of molecular systems for quantum chemical methods and several recent applications. The general goal is to highlight both the value and limitations of SE methods and stimulate further developments that allow them to effectively complement ab initio methods in the analysis of complex molecular systems.

Revision of the GROMOS 56A6(CARBO) force field: Improving the description of ring-conformational equilibria in hexopyranose-based carbohydrates chains

This article describes a revised version 56A6(CARBO_R) of the GROMOS 56A6(CARBO) force field for hexopyranose-based carbohydrates. The simulated properties of unfunctionalized hexopyranoses are unaltered with respect to 56A6CARBO . In the context of both O1 -alkylated hexopyranoses and oligosaccharides, the revision stabilizes the regular (4) C1 chair for α-anomers, with the opposite effect for β-anomers. As a result, spurious ring inversions observed in α(1→4)-linked chains when using the original 56A6(CARBO) force field are alleviated. The (4) C1 chair is now the most stable conformation for all d-hexopyranose residues, irrespective of the linkage type and anomery, and of the position of the residue along the chain. The methylation of a d-hexopyranose leads to a systematic shift in the ring-inversion free energy ((4) C1 to (1) C4 ) by 7-8 kJ mol(-1), positive for the α-anomers and negative for the β-anomers, which is qualitatively compatible with the expected enhancement of the anomeric effect upon methylation at O1. The ring-inversion free energies for residues within chains are typically smaller in magnitude compared to those of the monomers, and correlate rather poorly with the latter. This suggests that the crowding of ring substituents upon chain formation alters the ring flexibility in a nonsystematic fashion. In general, the description of carbohydrate chains afforded by 56A6(CARBO_R) suggests a significant extent of ring flexibility, i.e., small but often non-negligible equilibrium populations of inverted chairs, and challenges the "textbook" picture of conformationally locked carbohydrate rings.

Enhanced semiempirical QM methods for biomolecular interactions

Recent successes and failures of the application of 'enhanced' semiempirical QM (SQM) methods are reviewed in the light of the benefits and backdraws of adding dispersion (D) and hydrogen-bond (H) correction terms. We find that the accuracy of SQM-DH methods for non-covalent interactions is very often reported to be comparable to dispersion-corrected density functional theory (DFT-D), while computation times are about three orders of magnitude lower. SQM-DH methods thus open up a possibility to simulate realistically large model systems for problems both in life and materials science with comparably high accuracy.