Natural Fragment Bond Orbital Method for Interfragment Bonding Interaction Analysis.

A complex chemical system is often examined based on their fragments, so fragment-based analysis is the key to chemical understanding. We report the natural fragment bond orbital (NFBO) method for interfragment bonding interaction analysis, as an extension to the well-known natural bond orbital method. NFBOs together with their corresponding natural fragment hybrid orbitals (NFHOs) allow us to derive local bonding and antibonding orbitals among fragments from the delocalized canonical molecular orbitals.

Fragment Aligned Molecular Orbital Analysis: An Innovative Tool for Analyzing Atypical Chemical Bonding.

In chemical research, it is a common practice to carry out quantum chemical calculations and analyze the canonical molecular orbitals (CMOs) obtained to study electronic structures of chemical systems. However, extensive orbital mixing of CMOs especially in molecular clusters significantly complicates our understanding of the electronic structures. In this paper, we have developed an innovative tool called fragment aligned molecular orbital (FAMO) analysis, which reconstructs our modular chemical picture by making use of the Procrustes analysis in statistical theory to align the occupied molecular orbitals of a molecular species against the occupied (molecular) orbitals of the constituting fragments of the cluster, and results in a set of chemically intuitive semilocalized orbitals.

Marriage of High-Throughput Gradient Surface Generation With Statistical Learning for the Rational Design of Functionalized Biomaterials.

Functional biomaterial is already an important aspect in modern therapeutics; yet, the design of novel multi-functional biomaterial is still a challenging task nowadays. When several biofunctional components are present, the complexity that arises from their combinations and interactions will lead to tedious trial-and-error screening. In this work, a novel strategy of biomaterial rational design through the marriage of gradient surface generation with statistical learning is presented.

Reactivity of Unsupported Transition Metal-Aluminyl Complexes: A Nucleophilic TM-Al Bond.

Despite the long history of research in transition metal (TM) complexes, the study of TM-aluminyl complexes is still in its early stage of development. It is expected that the presence of an electropositive Al donor atom would open up new possibilities in TM complex reactivity, and indeed TM-aluminyl has shown an early sign of success in small-molecule activation. On the other hand, the existing reports on TM-aluminyl reactivity are often explained to readers with different understanding on individual cases, and a general picture of TM-aluminyl reactivity is still not available.

Elucidation of the key role of Pt···Pt interactions in the directional self-assembly of platinum(II) complexes.

Here, we report the use of an amphiphilic Pt(II) complex, K[Pt{(O3SCH2CH2CH2)2bzimpy}Cl] (PtB), as a model to elucidate the key role of Pt···Pt interactions in directing self-assembly by combining temperature-dependent ultraviolet-visible (UV-Vis) spectroscopy, stopped-flow kinetic experiments, quantum mechanics (QM) calculations, and molecular dynamics (MD) simulations. Interestingly, we found that the self-assembly mechanism of PtB in aqueous solution follows a nucleation-free isodesmic model, as revealed by the temperature-dependent UV-Vis experiments. In contrast, a cooperative growth is found for the self-assembly of PtB in acetone–water (7:1, vol/vol) solution, which is further verified by the stopped-flow experiments, which clearly indicates the existence of a nucleation phase in the acetone–water (7:1, vol/vol) solution.

RPnet: a reverse-projection-based neural network for coarse-graining metastable conformational states for protein dynamics.

The Markov State Model (MSM) is a powerful tool for modeling long timescale dynamics based on numerous short molecular dynamics (MD) simulation trajectories, which makes it a useful tool for elucidating the conformational changes of biological macromolecules. By partitioning the phase space into discretized states and estimating the probabilities of inter-state transitions based on short MD trajectories, one can construct a kinetic network model that could be used to extrapolate long-timescale kinetics if the Markovian condition is met. However, meeting the Markovian condition often requires hundreds or even thousands of states (microstates), which greatly hinders the comprehension of the conformational dynamics of complex biomolecules.

Accurate Analysis of Anisotropic Carrier Mobility and Structure-property Relationships in Organic BOXD Crystalline Materials.

Charge mobility is an essential factor of organic crystalline materials. Although many investigators have made important progress, the exact relationship between the crystal structure and carrier mobility remains to be clarified. Fortunately, a series of bis-1,3,4-oxadiazole derivatives have been successfully prepared and reported.

Microsecond timescale MD simulations at the transition state of HMGR predict remote allosteric residues.

Understanding the mechanisms of enzymatic catalysis requires a detailed understanding of the complex interplay of structure and dynamics of large systems that is a challenge for both experimental and computational approaches. More importantly, the computational demands of QM/MM simulations mean that the dynamics of the reaction can only be considered on a timescale of nanoseconds even though the conformational changes needed to reach the catalytically active state happen on a much slower timescale. Here we demonstrate an alternative approach that uses transition state force fields (TSFFs) derived by the quantum-guided molecular mechanics (Q2MM) method that provides a consistent treatment of the entire system at the classical molecular mechanics level and allows simulations at the microsecond timescale.

Superatomic Ligand-Field Splitting in Ligated Gold Nanoclusters.

Gold nanoclusters are attractive because of their electronic and optical properties. Many theoretical models have been proposed to explain their electronic structures through an electron-counting approach. However, subtle features may not be well explained by electron-counting rules.

Principal interacting spin orbital: understanding the fragment interactions in open-shell systems.

Due to the recent rise in the interest and research efforts on first-row transition metal catalysis and other radical-related reactions, open-shell systems play a much more important role in modern chemistry. However, the development of bonding analysis tools for open-shell systems is still lagging behind. In this work, we present the principal interacting spin orbital (PISO) analysis, which is an analysis framework developed based on our previously reported principal interacting orbital (PIO) analysis.

A deep learning framework to predict binding preference of RNA constituents on protein surface.

Protein-RNA interaction plays important roles in post-transcriptional regulation. However, the task of predicting these interactions given a protein structure is difficult. Here we show that, by leveraging a deep learning model NucleicNet, attributes such as binding preference of RNA backbone constituents and different bases can be predicted from local physicochemical characteristics of protein structure surface.

Inter-ligand delocalisations in transition metal complexes containing multiple non-innocent ligands.

Systematic bonding analysis has been carried out for transition metal complexes containing more than one redox-active/non-innocent ligand. These complexes include tetralithio spiroaromatic palladole, dicupra[10]annulene, highly reduced nickel cyclooctadiene complex and tris(dithiolene)vanadium(iv). Our detailed bonding analysis reveals a common inter-ligand delocalisation pattern in these cases.

Intrinsic Cleavage of RNA Polymerase II Adopts a Nucleobase-independent Mechanism Assisted by Transcript Phosphate.

RNA polymerase II (Pol II) utilises the same active site for polymerization and intrinsic cleavage. Pol II proofreads the nascent transcript by its intrinsic nuclease activity to maintain high transcriptional fidelity critical for cell growth and viability. The detailed catalytic mechanism of intrinsic cleavage remains unknown.

Remote Bonding in Clusters [PdGeR]: Modular Bonding Model for Large Clusters via Principal Interacting Orbital Analysis.

Main group cluster compounds have attracted increasing attention in the past decades. Despite recent developments in their synthesis, the description of their electronic structures is usually limited to simply applying Wade's rule originally developed for borane compounds. This traditional approach is once again challenged by two recently reported group 14 metalloid clusters in the form of [PdGeR].

Revitalizing Spin Natural Orbital Analysis: Electronic Structures of Mixed-Valence Compounds, Singlet Biradicals, and Antiferromagnetically Coupled Systems.

Chemical systems with open-shell electronic structure have been gaining attention these days. Their potential applications in first-row transition metal catalysis, molecular wires, photovoltaics and other potential applications have urged the adoption of a simple analysis tool to better understand their open-shell electronic structures, especially the role played by the unpaired electrons. Despite its lack of popularity, spin natural orbital (SNO) analysis is a tool we found to well-suit this purpose.

An efficient Bayesian kinetic lumping algorithm to identify metastable conformational states via Gibbs sampling.

Markov State Model (MSM) has become a popular approach to study the conformational dynamics of complex biological systems in recent years. Built upon a large number of short molecular dynamics simulation trajectories, MSM is able to predict the long time scale dynamics of complex systems. However, to achieve Markovianity, an MSM often contains hundreds or thousands of states (microstates), hindering human interpretation of the underlying system mechanism.

Unravelling Chemical Interactions with Principal Interacting Orbital Analysis.

Decomposing chemical interactions into bonds and other higher order interactions is a common practice to analyse chemical structures, and gave birth to many chemical concepts, despite the fact that the decomposition itself might be subjective in nature. Fragment molecular orbitals (FMOs) offer a more rigorous alternative to such intuition, but might be less interpretable due to extensive delocalisation in FMOs. Inspired by the Principal Component Analysis in statistics, we hereby present a novel framework, Principal Interacting Orbital (PIO) analysis, that can very quickly identify the "dominant interacting orbitals" that are semi-localised and easily interpretable, while still maintaining mathematical rigor.

Isolation and enantiostability of the B-chiral bis(salicylato)borate anions [B (Sal)] and [B (Sal)].

The chiral spiroborate anions [B (Sal)] and [B (Sal)], ( and subscripts indicate boron stereochemistry) have been isolated as 1 : 1 quininium and 1 : 2 sparteinium salts, [HQuin][B (Sal)] and [HSpa][B (Sal)] respectively, by either cation metathesis or a simple one-pot synthesis involving reaction of boric and salicylic acids with the alkaloid base. Circular dichroism (CD) spectroscopy shows that the B-based chirality is stable in polar aprotic media, such as DMF or DMSO, though labile in protic solutions. Enantiopure salts with achiral counter-cations such as [NBu][B (Sal)] may then be prepared by exchange, so these B-chiral anions may have use in metathesis-based resolutions.

Path lumping: An efficient algorithm to identify metastable path channels for conformational dynamics of multi-body systems.

Constructing Markov state models from large-scale molecular dynamics simulation trajectories is a promising approach to dissect the kinetic mechanisms of complex chemical and biological processes. Combined with transition path theory, Markov state models can be applied to identify all pathways connecting any conformational states of interest. However, the identified pathways can be too complex to comprehend, especially for multi-body processes where numerous parallel pathways with comparable flux probability often coexist.

Structure and bonding of [PdSn]: an interesting example of the mutual delocalisation phenomenon.

In this article, we have presented a computational analysis on the structure and bonding of [PdSn] and illustrated that it serves as an interesting example of OMO-UMO mutual delocalisation with two identical [PdE] fragments. We have also illustrated the alternative roles that could be played by an [ME]/[E] fragment, a simple L-type donor and a lone-pair acceptor.

Adaptive partitioning by local density-peaks: An efficient density-based clustering algorithm for analyzing molecular dynamics trajectories.

We present an efficient density-based adaptive-resolution clustering method APLoD for analyzing large-scale molecular dynamics (MD) trajectories. APLoD performs the k-nearest-neighbors search to estimate the density of MD conformations in a local fashion, which can group MD conformations in the same high-density region into a cluster. APLoD greatly improves the popular density peaks algorithm by reducing the running time and the memory usage by 2-3 orders of magnitude for systems ranging from alanine dipeptide to a 370-residue Maltose-binding protein.

An [Au] Approach to the Study of Gold Nanoclusters.

Recently, many examples of gold nanoclusters have been synthesized due to their exceptional spectroscopic properties and potential applications in nanotechnology. In this work we put forward an approach based on the icosahedral [Au] unit and summarize three possible extensions of the unit: wrapping, bonding, and vertex sharing. We show that the electronic structure of such clusters can be treated in a more localized manner and show how the approach could be applied to understand the structure and bonding of a large variety of gold nanoclusters.

Understanding the core of RNA interference: The dynamic aspects of Argonaute-mediated processes.

At the core of RNA interference, the Argonaute proteins (Ago) load and utilize small guide nucleic acids to silence mRNAs or cleave foreign nucleic acids in a sequence specific manner. In recent years, based on extensive structural studies of Ago and its interaction with the nucleic acids, considerable progress has been made to reveal the dynamic aspects of various Ago-mediated processes. Here we review these novel insights into the guide-strand loading, duplex unwinding, and effects of seed mismatch, with a focus on two representative Agos, the human Ago 2 (hAgo2) and the bacterial Thermus thermophilus Ago (TtAgo).

Elucidation of the conformational dynamics of multi-body systems by construction of Markov state models.

Constructing Markov State Models (MSMs) based on short molecular dynamics simulations is a powerful computational technique to complement experiments in predicting long-time kinetics of biomolecular processes at atomic resolution. Even though the MSM approach has been widely applied to study one-body processes such as protein folding and enzyme conformational changes, the majority of biological processes, e.g.