Comparisons of different force fields in conformational analysis and searching of organic molecules: A review

Deciphering molecular structures: NMR spectroscopy and quantum mechanical insights of halogenated 4H-Chromenediones

Sesquiterpene lactones (SL) represent a class of secondary metabolites found in the Asteraceae family, notable for their unique structures. The SL α-santonin (1) and its derivatives are worthy of mention due to their diverse biological properties. Additionally, 4H-chromenes and 4H-chromones are appealing frameworks holding the capability to be used as structural motifs for new drugs. Furthermore, unambiguous structural elucidation is crucial for developing novel compounds for diverse applications. In this context, it is common to find in the literature molecules erroneously assigned. Therefore, the use of quantum mechanical calculations to simulate NMR chemical shifts has emerged as a valuable strategy. In this work, we conceived the synthesis of two halogenated 4H-chromenediones derived from photosantonic acid (2), a photoproduct arising from irradiation of α-santonin (1) in the ultraviolet region. The structure of the chlorinated and brominated products was determined by NMR analysis, with the aid of quantum mechanical calculations at the B3LYP/6-311 + G(2d,p)//M062x/6-31 + G(d,p) level of theory. All analyses were in agreement and led to the assignment of the brominated 4H-chromene-2,7-dione as (3S,3aS,5aR,9bS)-5a-(2-bromopropan-2-yl)-3-methyl-3,3a,5,5a,8,9b-hexahydro-4H-furo[2,3-f]chromene-2,7-dione (11b) and of the chlorinated 4H-chromene-2,7-dione as (3S,3aS,5aR,9bS)-5a-(2-chloropropan-2-yl)-3-methyl-3,3a,5,5a,8,9b-hexahydro-4H-furo[2,3-f]chromene-2,7-dione (12b). The diastereoselectivities of the reactions were explained based on products and intermediates formation energy calculated using B3LYP/6-31 + G(d,p) as the level of theory. Structures 11b and 12b were identified as the thermodynamic and kinetic products of the reaction among all candidates. Consequently, the strategy utilized in this study is robust and successfully illustrates the use of quantum mechanical calculations in the structural elucidation of new compounds with potential applications as novel drugs or products.

Emerging Conformational-Analysis Protocols from the RTCONF55-16K Reaction Thermochemistry Conformational Benchmark Set

RTCONF55-16K is a new, reactive conformational data set based on cost-efficient methods to assess different conformational analysis protocols. Our reference calculations underpinned the accuracy of the CENSO (Grimme et al. J. Phys. Chem. A, 2021, 125, 4039) procedure and resulted in alternative recipes with different cost-accuracy compromises. Our general-purpose and economical protocols (CENSO-light and zero, respectively) were found to be 10-30 times faster than the original algorithm, adding only 0.4-0.7 kcal/mol absolute error to the relative free energy estimates.

Taming the cytokine storm: small molecule inhibitors targeting IL-6/IL-6α receptor

Given the increasing effectiveness of immune-based therapies, management of their associated toxicities is of utmost importance. Cytokine release syndrome (CRS), characterized by elevated levels of cytokine, poses a significant challenge following the administration of antibodies and CAR-T cell therapies. CRS also contributes to multiple organ dysfunction in severe viral infections, notably in COVID-19. Given the pivotal role of IL-6 cytokine in initiating CRS, it has been considered a most potential therapeutic target to mitigate hyperactivated immune responses. While monoclonal antibodies of IL-6 show promise in mitigating cytokine storm, concerns about immunotoxicity persist, and small molecule IL-6 antagonists remain unavailable. The present study employed sophisticated computational techniques to identify potential hit compounds as IL-6 inhibitors, with the aim of inhibiting IL-6/IL-6R protein-protein interactions. Through ligand-based pharmacophore mapping and shape similarity in combination with docking-based screening, we identified nine hit compounds with diverse chemical scaffolds as potential binders of IL-6. Further, the MD simulation of 300 ns of five virtual hits in a complex with IL-6 was employed to study the dynamic behavior. To provide a more precise prediction, binding free energy was also estimated. The identified compounds persistently interacted with the residues lining the binding site of the IL-6 protein. These compounds displayed low binding energy during MMPBSA calculations, substantiating their strong association with IL-6. This study suggests promising scaffolds as potential inhibitors of IL-6/IL-6R protein-protein interactions and provides direction for lead optimization.

Long but Strong C-C Single Bonds: Challenges for Theory

Theoretical challenges in describing molecules with anomalously long single C-C bonds are analyzed in terms of the relative contributions of stabilizing and destabilizing intramolecular interactions. Diamondoid dimers that are stable despite the presence of C-C bonds up to 1.7 Å long, as well as other bulky molecules stabilized due to intramolecular noncovalent interactions (London dispersions) are discussed. The unexpected stability of highly crowded molecules, such as diamondoid dimers and tert-butyl-substituted hexaphenylethanes, calls for reconsideration of the "steric effect" traditionally thought to destabilize the molecule. Alternatively, "steric attraction" helps to understand bonding in sterically overloaded molecules, whose structural and energetic analysis requires a proper theoretical description of noncovalent interactions.

Computational approaches to investigate fluoride binding, selectivity and transport across the membrane

The use of molecular dynamics (MD) simulations to study biomolecular systems has proven reliable in elucidating atomic-level details of structure and function. In this chapter, MD simulations were used to uncover new insights into two phylogenetically unrelated bacterial fluoride (F-) exporters: the CLCF F-/H+ antiporter and the Fluc F- channel. The CLCF antiporter, a member of the broader CLC family, has previously revealed unique stoichiometry, anion-coordinating residues, and the absence of an internal glutamate crucial for proton import in the CLCs. Through MD simulations enhanced with umbrella sampling, we provide insights into the energetics and mechanism of the CLCF transport process, including its selectivity for F- over HF. In contrast, the Fluc F- channel presents a novel architecture as a dual topology dimer, featuring two pores for F- export and a central non-transported sodium ion. Using computational electrophysiology, we simulate the electrochemical gradient necessary for F- export in Fluc and reveal details about the coordination and hydration of both F- and the central sodium ion. The procedures described here delineate the specifics of these advanced techniques and can also be adapted to investigate other membrane protein systems.

Conformational energies of reference organic molecules: benchmarking of common efficient computational methods against coupled cluster theory

We selected 145 reference organic molecules that include model fragments used in computer-aided drug design. We calculated 158 conformational energies and barriers using force fields, with wide applicability in commercial and free softwares and extensive application on the calculation of conformational energies of organic molecules, e.g. the UFF and DREIDING force fields, the Allinger's force fields MM3-96, MM3-00, MM4-8, the MM2-91 clones MMX and MM+, the MMFF94 force field, MM4, ab initio Hartree-Fock (HF) theory with different basis sets, the standard density functional theory B3LYP, the second-order post-HF MP2 theory and the Domain-based Local Pair Natural Orbital Coupled Cluster DLPNO-CCSD(T) theory, with the latter used for accurate reference values. The data set of the organic molecules includes hydrocarbons, haloalkanes, conjugated compounds, and oxygen-, nitrogen-, phosphorus- and sulphur-containing compounds. We reviewed in detail the conformational aspects of these model organic molecules providing the current understanding of the steric and electronic factors that determine the stability of low energy conformers and the literature including previous experimental observations and calculated findings. While progress on the computer hardware allows the calculations of thousands of conformations for later use in drug design projects, this study is an update from previous classical studies that used, as reference values, experimental ones using a variety of methods and different environments. The lowest mean error against the DLPNO-CCSD(T) reference was calculated for MP2 (0.35 kcal mol-1), followed by B3LYP (0.69 kcal mol-1) and the HF theories (0.81-1.0 kcal mol-1). As regards the force fields, the lowest errors were observed for the Allinger's force fields MM3-00 (1.28 kcal mol-1), ΜΜ3-96 (1.40 kcal mol-1) and the Halgren's MMFF94 force field (1.30 kcal mol-1) and then for the MM2-91 clones MMX (1.77 kcal mol-1) and MM+ (2.01 kcal mol-1) and MM4 (2.05 kcal mol-1). The DREIDING (3.63 kcal mol-1) and UFF (3.77 kcal mol-1) force fields have the lowest performance. These model organic molecules we used are often present as fragments in drug-like molecules. The values calculated using DLPNO-CCSD(T) make up a valuable data set for further comparisons and for improved force field parameterization.

Reformulating Reactivity Design for Data-Efficient Machine Learning

Machine learning (ML) can deliver rapid and accurate reaction barrier predictions for use in rational reactivity design. However, model training requires large data sets of typically thousands or tens of thousands of barriers that are very expensive to obtain computationally or experimentally. Furthermore, bespoke data sets are required for each region of interest in reaction space as models typically struggle to generalize. We have therefore reformulated the ML barrier prediction problem toward a much more data-efficient process: finding a reaction from a prespecified set with a desired target value. Our reformulation enables the rapid selection of reactions with purpose-specific activation barriers, for example, in the design of reactivity and selectivity in synthesis, catalyst design, toxicology, and covalent drug discovery, requiring just tens of accurately measured barriers. Importantly, our reformulation does not require generalization beyond the domain of the data set at hand, and we show excellent results for the highly toxicologically and synthetically relevant data sets of aza-Michael addition and transition-metal-catalyzed dihydrogen activation, typically requiring less than 20 accurately measured density functional theory (DFT) barriers. Even for incomplete data sets of E2 and SN2 reactions, with high numbers of missing barriers (74% and 56% respectively), our chosen ML search method still requires significantly fewer data points than the hundreds or thousands needed for more conventional uses of ML to predict activation barriers. Finally, we include a case study in which we use our process to guide the optimization of the dihydrogen activation catalyst. Our approach was able to identify a reaction within 1 kcal mol-1 of the target barrier by only having to run 12 DFT reaction barrier calculations, which illustrates the usage and real-world applicability of this reformulation for systems of high synthetic importance.

Lead identification against Mycobacterium tuberculosis using highly enriched active molecules against pantothenate synthetase

The Pantothenate synthetase (PS) from the Mycobacterium tuberculosis (Mtb) holds a crucial role in the survival and robust proliferation of bacteria through its catalysis of coenzyme A and acyl carrier protein synthesis. The present study undertook the PS drug target in complex with a co-crystallized ligand and subjected it to docking and virtual screening approaches. The experimental design encompassed three discrete datasets: an active dataset featuring 136 compounds, an inactive dataset comprising 56 compounds, and a decoys dataset curated from the zinc library, comprising an extensive compilation of approximately 53,000 compounds. The compounds' binding energies were observed to be in the range of -5 to ∼-14 kcal/mol. Additionally, binding energy results were further refined through Enrichment Factor analysis (EF). EF is a new statistical approach which uses the scores obtained from docking-based virtual screening and predicts the precision of the scoring function. Remarkably, the Enrichment Factor (EF) analysis produced exceptionally favorable outcomes, attaining an EF of approximately 49% within the uppermost 1% fraction of the compound distribution. Finally, a total of eight compounds, evenly distributed between the active dataset and the decoys dataset, emerged as potent inhibitors of the Pantothenate synthetase (PS) enzyme. The analysis of inhibition constants and binding energy revealed a notable correlation, with an r-squared value (r2) of 0.912 between the two parameters. Furthermore, the shortlisted compounds were subjected to 100 ns MD simulation to determine their stability and dynamics behavior. The decoy compounds that have been identified, exhibiting properties comparable to the active compounds, are postulated as potential candidates for targeting the Pantothenate synthetase (PS) enzyme to treat Mtb infection. Nevertheless, in the pursuit of a comprehensive investigation, it is advisable to undertake additional experimental validation as a component of the subsequent study.Communicated by Ramaswamy H. Sarma.

A General Picture of Cucurbit[8]uril Host–Guest Binding: Recalibrating Bonded Interactions

Atomic-level understanding of the dynamic feature of host–guest interactions remains a central challenge in supramolecular chemistry. The remarkable guest binding behavior of the Cucurbiturils family of supramolecular containers makes them promising drug carriers. Among Cucurbit[n]urils, Cucurbit[8]uril (CB8) has an intermediate portal size and cavity volume. It can exploit almost all host–guest recognition motifs formed by this host family. In our previous work, an extensive computational investigation of the binding of seven commonly abused and structurally diverse drugs to the CB8 host was performed, and a general dynamic binding picture of CB8-guest interactions was obtained. Further, two widely used fixed-charge models for drug-like molecules were investigated and compared in great detail, aiming at providing guidelines in choosing an appropriate charge scheme in host-guest modelling. Iterative refitting of atomic charges leads to improved binding thermodynamics and the best root-mean-squared deviation from the experimental reference is 2.6 kcal/mol. In this work, we focus on a thorough evaluation of the remaining parts of classical force fields, i.e., the bonded interactions. The widely used general Amber force fields are assessed and refitted with generalized force-matching to improve the intra-molecular conformational preference, and thus the description of inter-molecular host–guest interactions. The interaction pattern and binding thermodynamics show a significant dependence on the modelling parameters. The refitted system-specific parameter set improves the consistency of the modelling results and the experimental reference significantly. Finally, combining the previous charge-scheme comparison and the current force-field refitting, we provide general guidelines for the theoretical modelling of host–guest binding.

An Imbalance in the Force: The Need for Standardized Benchmarks for Molecular Simulation

Force fields (FFs) for molecular simulation have been under development for more than half a century. As with any predictive model, rigorous testing and comparisons of models critically depends on the availability of standardized data sets and benchmarks. While such benchmarks are rather common in the fields of quantum chemistry, this is not the case for empirical FFs. That is, few benchmarks are reused to evaluate FFs, and development teams rather use their own training and test sets. Here we present an overview of currently available tests and benchmarks for computational chemistry, focusing on organic compounds, including halogens and common ions, as FFs for these are the most common ones. We argue that many of the benchmark data sets from quantum chemistry can in fact be reused for evaluating FFs, but new gas phase data is still needed for compounds containing phosphorus and sulfur in different valence states. In addition, more nonequilibrium interaction energies and forces, as well as molecular properties such as electrostatic potentials around compounds, would be beneficial. For the condensed phases there is a large body of experimental data available, and tools to utilize these data in an automated fashion are under development. If FF developers, as well as researchers in artificial intelligence, would adopt a number of these data sets, it would become easier to compare the relative strengths and weaknesses of different models and to, eventually, restore the balance in the force.

Impacts of noncovalent interactions involving sulfur atoms on protein stability, structure, folding, and bioactivity

This review discusses the various types of noncovalent interactions in which sulfur atoms participate and their effects on protein stability, structure, folding and bioactivity. Current approaches and recommendations for modelling these noncovalent interactions (in terms of both geometries and interaction energies) are highlighted.

Strebluses E-H, four new stilbene-like derivatives from the stems of Streblus ilicifolius

Following bioactivity-guided isolation, four new stilbene-like derivatives, named Strebluses E-H, were isolated from the EtOAc-soluble fraction of the stems of Streblus ilicifolius (Moraceae). Their chemical structures were elucidated based on NMR spectroscopic data interpretation and optical rotation calculation. Streblus E possesses potent tyrosinase inhibitory activity with an IC₅₀ value of 0.1 μM. Oxy-tyrosinase has two bound Cu²⁺ ions and a peroxide group in the binding site, which has a role in the catalytic oxidation. Thus, a docking study of Streblus E with oxy-tyrosinase was performed to analyze the ligand-protein interactions. With in silico modelling, the S value and the ligand-protein interactions suggested that Streblus E showed lower binding affinity for oxy-tyrosinase than that of Streblus C.

A New abeo-Icetexane-Type Diterpenoid from the Stem Barks of Taxus wallichiana

From a CH2 Cl2 -soluble fraction of the stem barks of Taxus wallichiana, one new abeo-icetexane-type diterpenoid, taxamairin I (1), was isolated. Its absolute configuration was elucidated based on spectroscopic interpretation and time-dependent density functional theory (TD-DFT) calculation of optical rotation. In addition, the plausible biosynthesis pathway for the formation of the new abeo-icetexane-type diterpenoid was proposed. Taxamairin I (1), at a concentration of 100 μM, did not show cytotoxicity against Hep3B human liver cancer cell lines.

May the Force (Field) Be with You: On the Importance of Conformational Searches in the Prediction of NMR Chemical Shifts

NMR data prediction is increasingly important in structure elucidation. The impact of force field selection was assessed, along with geometry and energy cutoffs. Based on the conclusions, we propose a new approach named mix-J-DP4, which provides a remarkable increase in the confidence level of complex stereochemical assignments-100% in our molecular test set-with a very modest increment in computational cost.

Comparing the Performances of Force Fields in Conformational Searching of Hydrogen-Bond-Donating Catalysts

Here, we compare the relative performances of different force fields for conformational searching of hydrogen-bond-donating catalyst-like molecules. We assess the force fields by their predictions of conformer energies, geometries, low-energy, nonredundant conformers, and the maximum numbers of possible conformers. Overall, MM3, MMFFs, and OPLS3e had consistently strong performances and are recommended for conformationally searching molecules structurally similar to those in this study.

Experimental and theoretical study of novel aminobenzamide–aminonaphthalimide fluorescent dyads with a FRET mechanism

In this work, both experimental and theoretical methods were used to study the photophysical and metal ion binding properties of a series of new aminobenzamide–aminonaphthalimide (2ABZ–ANAPIM) fluorescent dyads. The 2-aminobenzamide (2ABZ) and 6-aminonaphthalimide (ANAPIM) fluorophores were linked through alkyl chains (C₂ to C₆) to obtain four fluorescent dyads. These dyads present a highly efficient (0.61 to 0.98) Förster Resonant Energy Transfer (FRET) from the 2ABZ to the ANAPIM due to the 2ABZ emission and ANAPIM excitation band overlap and the configurational stacking of both aromatic systems which allows the energy transfer. These dyads interact with Cu²⁺ and Hg²⁺ metal ions in solution inhibiting the FRET mechanism by the cooperative coordination of both 2ABZ and ANAPIM moieties. Both experimental and theoretical results are consistent and describe clearly the photophysical and coordination properties of these new dyads.

The aminobenzamide–aminonaphthalimide fluorescent dyads allow the determination of Cu²⁺ and Hg²⁺ metal ion concentration from Förster Resonant Energy Transfer measurements.

ECD exciton chirality method today: a modern tool for determining absolute configurations

The application of the exciton chirality method (ECM) to interpret electronic circular dichroism (ECD) spectra is a well‐established and still popular approach to assign the absolute configuration (AC) of natural products, chiral organic compounds, and organometallic species. The method applies to compounds containing at least two chromophores with electric dipole allowed transitions (e.g., π–π* transitions). The exciton chirality rule correlates the sign of an exciton couplet (two ECD bands with opposite sign and similar intensity) with the overall molecular stereochemistry, including the AC. A correct application of the ECM requires three main prerequisites: (a) the knowledge of the molecular conformation, (b) the knowledge of the directions of the electric transition moments (TDMs), and (c) the assumption that the exciton coupling mechanism must be the major source of the observed ECD signals. All these prerequisites can be easily verified by means of quantum‐mechanical (QM) calculations. In the present review, we shortly introduce the general principles that underpin the use of the ECM for configurational assignments and survey its applications, both classic ones and some reported in the recent literature. Based on these examples, we will stress the advantages of the ECM but also the key requisites for its correct application. Additionally, we will discuss the dependence of the couplet sign on geometrical parameters (angles α,β,γ between TDMs), which can be helpful for discerning the sign of exciton chirality in ambiguous situations. Finally, we will present a molecular orbital (MO) description of the exciton coupling phenomenon.

Automated Exploration of Prebiotic Chemical Reaction Space: Progress and Perspectives

Prebiotic chemistry often involves the study of complex systems of chemical reactions that form large networks with a large number of diverse species. Such complex systems may have given rise to emergent phenomena that ultimately led to the origin of life on Earth. The environmental conditions and processes involved in this emergence may not be fully recapitulable, making it difficult for experimentalists to study prebiotic systems in laboratory simulations. Computational chemistry offers efficient ways to study such chemical systems and identify the ones most likely to display complex properties associated with life. Here, we review tools and techniques for modelling prebiotic chemical reaction networks and outline possible ways to identify self-replicating features that are central to many origin-of-life models.

Molecular dynamics: a powerful tool for studying the medicinal chemistry of ion channel modulators

Molecular dynamics (MD) simulations allow researchers to investigate the behavior of desired biological targets at ever-decreasing costs with ever-increasing precision. Among the biological macromolecules, ion channels are remarkable transmembrane proteins, capable of performing special biological processes and revealing a complex regulatory matrix, including modulation by small molecules, either endogenous or exogenous. Recently, given the developments in ion channel structure determination and accessibility of bio-computational techniques, MD and related tools are becoming increasingly popular in the intense research area regarding ligand-channel interactions. This review synthesizes and presents the most important fields of MD involvement in investigating channel-molecule interactions, including, but not limited to, deciphering the binding modes of ligands to their ion channel targets and the mechanisms through which chemical compounds exert their effect on channel function. Special attention is devoted to the importance of more elaborate methods, such as free energy calculations, while principles regarding drug design and discovery are highlighted. Several technical aspects involving the creation and simulation of channel-molecule MD systems (ligand parameterization, proper membrane setup, system building, etc.) are also presented.

Convenient Synthesis of Pyrazolo[4',3':5,6]pyrano[4,3-c][1,2]oxazoles via Intramolecular Nitrile Oxide Cycloaddition

A simple and efficient synthetic route to the novel 3a,4-dihydro-3H,7H- and 4H,7H-pyrazolo[4′,3′:5,6]pyrano[4,3-c][1,2]oxazole ring systems from 3-(prop-2-en-1-yloxy)- or 3-(prop-2-yn-1-yloxy)-1H-pyrazole-4-carbaldehyde oximes has been developed by employing the intramolecular nitrile oxide cycloaddition (INOC) reaction as the key step. The configuration of intermediate aldoximes was unambiguously determined using NOESY experimental data and comparison of the magnitudes of ¹J_CH coupling constants of the iminyl moiety, which were greater by approximately 13 Hz for the predominant syn isomer. The structures of the obtained heterocyclic products were confirmed by detailed ¹H, ¹³C and ¹⁵N NMR spectroscopic experiments and HRMS measurements.

Tyrosinase Inhibitors from the Stems of Streblus Ilicifolius

Two new stilbene derivatives, named strebluses C and D, were isolated from the EtOAc-soluble fraction of the stems of Streblus ilicifolius (Moraceae). Its absolute configuration was elucidated based on NMR spectroscopic data interpretation and optical rotation calculation. Streblus C possesses strong tyrosinase inhibitory activity with an IC₅₀ value of 0.01 μM. Docking studies of 1 and 2 with oxy-tyrosinase were carried out to analyze their interactions. The analysis of the docked poses confirmed that 1 showed better binding affinity for oxy-tyrosinase than that of 2.