Breaking the barriers of data scarcity in drug-target affinity prediction.

Accurate prediction of drug-target affinity (DTA) is of vital importance in early-stage drug discovery, facilitating the identification of drugs that can effectively interact with specific targets and regulate their activities. While wet experiments remain the most reliable method, they are time-consuming and resource-intensive, resulting in limited data availability that poses challenges for deep learning approaches. Existing methods have primarily focused on developing techniques based on the available DTA data, without adequately addressing the data scarcity issue. To overcome this challenge, we present the Semi-Supervised Multi-task training (SSM) framework for DTA prediction, which incorporates three simple yet highly effective strategies: (1) A multi-task training approach that combines DTA prediction with masked language modeling using paired drug-target data. (2) A semi-supervised training method that leverages large-scale unpaired molecules and proteins to enhance drug and target representations. This approach differs from previous methods that only employed molecules or proteins in pre-training. (3) The integration of a lightweight cross-attention module to improve the interaction between drugs and targets, further enhancing prediction accuracy. Through extensive experiments on benchmark datasets such as BindingDB, DAVIS and KIBA, we demonstrate the superior performance of our framework. Additionally, we conduct case studies on specific drug-target binding activities, virtual screening experiments, drug feature visualizations and real-world applications, all of which showcase the significant potential of our work. In conclusion, our proposed SSM-DTA framework addresses the data limitation challenge in DTA prediction and yields promising results, paving the way for more efficient and accurate drug discovery processes.

Identification of flexible Pif1-DNA interactions and their impacts on enzymatic activities.

Flexible regions in biomolecular complexes, although crucial to understanding structure-function relationships, are often unclear in high-resolution crystal structures. In this study, we showed that single-molecule techniques, in combination with computational modeling, can characterize dynamic conformations not resolved by high-resolution structure determination methods. Taking two Pif1 helicases (ScPif1 and BsPif1) as model systems, we found that, besides a few tightly bound nucleotides, adjacent solvent-exposed nucleotides interact dynamically with the helicase surfaces. The whole nucleotide segment possessed curved conformations and covered the two RecA-like domains of the helicases, which are essential for the inch-worm mechanism. The synergetic approach reveals that the interactions between the exposed nucleotides and the helicases could be reduced by large stretching forces or electrostatically shielded with high-concentration salt, subsequently resulting in reduced translocation rates of the helicases. The dynamic interactions between the exposed nucleotides and the helicases underlay the force- and salt-dependences of their enzymatic activities. The present single-molecule based approach complements high-resolution structural methods in deciphering the molecular mechanisms of the helicases.

Early-stage dynamics of chloride ion-pumping rhodopsin revealed by a femtosecond X-ray laser.

Chloride ion-pumping rhodopsin (ClR) in some marine bacteria utilizes light energy to actively transport Cl- into cells. How the ClR initiates the transport is elusive. Here, we show the dynamics of ion transport observed with time-resolved serial femtosecond (fs) crystallography using the Linac Coherent Light Source. X-ray pulses captured structural changes in ClR upon flash illumination with a 550 nm fs-pumping laser. High-resolution structures for five time points (dark to 100 ps after flashing) reveal complex and coordinated dynamics comprising retinal isomerization, water molecule rearrangement, and conformational changes of various residues. Combining data from time-resolved spectroscopy experiments and molecular dynamics simulations, this study reveals that the chloride ion close to the Schiff base undergoes a dissociation-diffusion process upon light-triggered retinal isomerization.

Crystal structures of agonist-bound human cannabinoid receptor CB1.

The cannabinoid receptor 1 (CB1) is the principal target of the psychoactive constituent of marijuana, the partial agonist Δ9-tetrahydrocannabinol (Δ9-THC). Here we report two agonist-bound crystal structures of human CB1 in complex with a tetrahydrocannabinol (AM11542) and a hexahydrocannabinol (AM841) at 2.80 Å and 2.95 Å resolution, respectively. The two CB1-agonist complexes reveal important conformational changes in the overall structure, relative to the antagonist-bound state, including a 53% reduction in the volume of the ligand-binding pocket and an increase in the surface area of the G-protein-binding region. In addition, a 'twin toggle switch' of Phe2003.36 and Trp3566.48 (superscripts denote Ballesteros-Weinstein numbering) is experimentally observed and appears to be essential for receptor activation. The structures reveal important insights into the activation mechanism of CB1 and provide a molecular basis for predicting the binding modes of Δ9-THC, and endogenous and synthetic cannabinoids. The plasticity of the binding pocket of CB1 seems to be a common feature among certain class A G-protein-coupled receptors. These findings should inspire the design of chemically diverse ligands with distinct pharmacological properties.

Mutations on RBD of SARS-CoV-2 Omicron variant result in stronger binding to human ACE2 receptor.

The COVID-19 pandemic caused by the SARS-CoV-2 virus has led to more than 270 million infections and 5.3 million of deaths worldwide. Several major variants of SARS-CoV-2 have emerged and posed challenges in controlling the pandemic. The recently occurred Omicron variant raised serious concerns about reducing the efficacy of vaccines and neutralization antibodies due to its vast mutations. We have modelled the complex structure of the human ACE2 protein and the receptor binding domain (RBD) of Omicron Spike protein (S-protein), and conducted atomistic molecular dynamics simulations to study the binding interactions. The analysis shows that the Omicron RBD binds more strongly to the human ACE2 protein than the original strain. The mutations at the ACE2-RBD interface enhance the tight binding by increasing hydrogen bonding interaction and enlarging buried solvent accessible surface area.

Crystal structure of rhodopsin bound to arrestin by femtosecond X-ray laser.

G-protein-coupled receptors (GPCRs) signal primarily through G proteins or arrestins. Arrestin binding to GPCRs blocks G protein interaction and redirects signalling to numerous G-protein-independent pathways. Here we report the crystal structure of a constitutively active form of human rhodopsin bound to a pre-activated form of the mouse visual arrestin, determined by serial femtosecond X-ray laser crystallography. Together with extensive biochemical and mutagenesis data, the structure reveals an overall architecture of the rhodopsin-arrestin assembly in which rhodopsin uses distinct structural elements, including transmembrane helix 7 and helix 8, to recruit arrestin. Correspondingly, arrestin adopts the pre-activated conformation, with a ∼20° rotation between the amino and carboxy domains, which opens up a cleft in arrestin to accommodate a short helix formed by the second intracellular loop of rhodopsin. This structure provides a basis for understanding GPCR-mediated arrestin-biased signalling and demonstrates the power of X-ray lasers for advancing the frontiers of structural biology.

Non-cryogenic structure of a chloride pump provides crucial clues to temperature-dependent channel transport efficiency.

Non-cryogenic protein structures determined at ambient temperature may disclose significant information about protein activity. Chloride-pumping rhodopsin (ClR) exhibits a trend to hyperactivity induced by a change in the photoreaction rate because of a gradual decrease in temperature. Here, to track the structural changes that explain the differences in CIR activity resulting from these temperature changes, we used serial femtosecond crystallography (SFX) with an X-ray free electron laser (XFEL) to determine the non-cryogenic structure of ClR at a resolution of 1.85 Å, and compared this structure with a cryogenic ClR structure obtained with synchrotron X-ray crystallography. The XFEL-derived ClR structure revealed that the all-trans retinal (ATR) region and positions of two coordinated chloride ions slightly differed from those of the synchrotron-derived structure. Moreover, the XFEL structure enabled identification of one additional water molecule forming a hydrogen bond network with a chloride ion. Analysis of the channel cavity and a difference distance matrix plot (DDMP) clearly revealed additional structural differences. B-factor information obtained from the non-cryogenic structure supported a motility change on the residual main and side chains as well as of chloride and water molecules because of temperature effects. Our results indicate that non-cryogenic structures and time-resolved XFEL experiments could contribute to a better understanding of the chloride-pumping mechanism of ClR and other ion pumps.

GDP Release from the Open Conformation of Gα Requires Allosteric Signaling from the Agonist-Bound Human ß2 Adrenergic Receptor.

G-protein-coupled receptors (GPCRs) transmit signals into the cell in response to ligand binding at its extracellular domain, which is characterized by the coupling of agonist-induced receptor conformational change to guanine nucleotide (GDP) exchange with guanosine triphosphate on a heterotrimeric (αßγ) guanine nucleotide-binding protein (G-protein), leading to the activation of the G-protein. The signal transduction mechanisms have been widely researched in vivo and in silico. However, coordinated communication from stimulating ligands to the bound GDP still remains elusive. In the present study, we used microsecond (µS) molecular dynamic (MD) simulations to directly probe the communication from the ß2 adrenergic receptor (ß2AR) with an agonist or an antagonist or no ligand to GDP bound to the open conformation of the Gα protein. Molecular mechanism-general Born surface area calculation results indicated either the agonist or the antagonist destabilized the binding between the receptor and the G-protein but the agonist caused a higher level of destabilization than the antagonist. This is consistent with the role of agonist in the activation of the G-protein. Interestingly, while GDP remained bound with the Gα-protein for the two inactive systems (antagonist-bound and apo form), GDP dissociated from the open conformation of the Gα protein for the agonist activated system. Data obtained from MD simulations indicated that the receptor and the Gα subunit play a big role in coordinated communication and nucleotide exchange. Based on residue interaction network analysis, we observed that engagement of agonist-bound ß2AR with an α5 helix of Gα is essential for the GDP release and the residues in the phosphate-binding loop, α1 helix, and α5 helix play very important roles in the GDP release. The insights on GPCR-G-protein communication will facilitate the rational design of agonists and antagonists that target both active and inactive GPCR binding pockets, leading to more precise drugs.

Serial time-resolved crystallography of photosystem II using a femtosecond X-ray laser.

Photosynthesis, a process catalysed by plants, algae and cyanobacteria converts sunlight to energy thus sustaining all higher life on Earth. Two large membrane protein complexes, photosystem I and II (PSI and PSII), act in series to catalyse the light-driven reactions in photosynthesis. PSII catalyses the light-driven water splitting process, which maintains the Earth's oxygenic atmosphere. In this process, the oxygen-evolving complex (OEC) of PSII cycles through five states, S0 to S4, in which four electrons are sequentially extracted from the OEC in four light-driven charge-separation events. Here we describe time resolved experiments on PSII nano/microcrystals from Thermosynechococcus elongatus performed with the recently developed technique of serial femtosecond crystallography. Structures have been determined from PSII in the dark S1 state and after double laser excitation (putative S3 state) at 5 and 5.5 Å resolution, respectively. The results provide evidence that PSII undergoes significant conformational changes at the electron acceptor side and at the Mn4CaO5 core of the OEC. These include an elongation of the metal cluster, accompanied by changes in the protein environment, which could allow for binding of the second substrate water molecule between the more distant protruding Mn (referred to as the 'dangler' Mn) and the Mn3CaOx cubane in the S2 to S3 transition, as predicted by spectroscopic and computational studies. This work shows the great potential for time-resolved serial femtosecond crystallography for investigation of catalytic processes in biomolecules.

Reversible rearrangement of magnetic nanoparticles in solution studied using time-resolved SAXS method.

Superparamagnetic nanoparticles have broad applications in biology and medicines. Quantitative measurements of magnetic beads in solution are essential in gaining comprehensive understanding of their dynamics and developing applications. Here, using synchrotron X-ray sources combined with well controlled magnetic fields, the results from small-angle X-ray scattering (SAXS) experiments on superparamagnetic particles in solution under the influence of external magnetic fields are reported. The particles mostly remain in monodispersed states and the linear aggregates tend to be aligned with the external magnetic field. After removing the magnetic fields, the superparamagnetic nanoparticles quickly recover to their original states indicating high reversibility of the rearrangement under the control of a magnetic field. The external magnetic field instrument composed of paired permanent magnets is integrated into the SAXS beamline at the Shanghai Synchrotron Radiation Facility providing a platform for studying time-resolved dynamics induced by magnetic fields.

The XFEL Protein Crystallography: Developments and Perspectives.

In the past 10 years, the world has witnessed the revolutionary development of X-ray free electron lasers (XFELs) and their applications in many scientific disciplinaries [...].

Non-Cryogenic Structure and Dynamics of HIV-1 Integrase Catalytic Core Domain by X-ray Free-Electron Lasers.

HIV-1 integrase (HIV-1 IN) is an enzyme produced by the HIV-1 virus that integrates genetic material of the virus into the DNA of infected human cells. HIV-1 IN acts as a key component of the Retroviral Pre-Integration Complex (PIC). Protein dynamics could play an important role during the catalysis of HIV-1 IN; however, this process has not yet been fully elucidated. X-ray free electron laser (XFEL) together with nuclear magnetic resonance (NMR) could provide information regarding the dynamics during this catalysis reaction. Here, we report the non-cryogenic crystal structure of HIV-1 IN catalytic core domain at 2.5 Å using microcrystals in XFELs. Compared to the cryogenic structure at 2.1 Å using conventional synchrotron crystallography, there was a good agreement between the two structures, except for a catalytic triad formed by Asp64, Asp116, and Glu152 (DDE) and the lens epithelium-derived growth factor binding sites. The helix III region of the 140-153 residues near the active site and the DDE triad show a higher dynamic profile in the non-cryogenic structure, which is comparable to dynamics data obtained from NMR spectroscopy in solution state.

IDPM: an online database for ion distribution in protein molecules.

BACKGROUND: Interactions between ions and proteins have been extensively studied, yet most of the studies focus on the ion binding site. The binding mechanism for many ion binding sites can be clearly described from high resolution structures. Although knowledge accumulated on a case-by-case basis is valuable, it is also important to study the ion-protein interaction statistically. From experimentally determined structures, it is possible to examine the ion distribution around each amino acid. Such distributions can reveal relation between ions and amino acids, so it is desirable to carry out a systematic survey of 'ion-amino acid' pairing interaction and share the information with a publicly available database. RESULTS: The survey in the Protein Data Bank (PDB) revealed that approximately 40% of molecules records contain at least one ion. To reduce the bias resulted from protein redundancy, the statistics were extracted from a non-redundant dataset by excluding the proteins with similar sequences. Based on the structures of protein molecules and the location of ions, the statistical distributions of ions around each proteinogenic amino acid type were investigated and further summarized in a database. To systematically quantify the interactions between ions and each amino acid, the positions of ions were mapped to the coordinate system centered at each neighboring amino acid. It was found that the distribution of ions follows the expected rules governed by the physicochemical interactions in general. Large variations were observed, reflecting the preference in 'ion-amino acid' interactions. The analysis program is written in the Python programming language. The statistical results and program are available from the online database: ion distribution in protein molecules (IDPM) at http://liulab.csrc.ac.cn/idpm/ . CONCLUSION: The spatial distribution of ions around amino acids is documented and analyzed. The statistics can be useful for identifying ion types for a given site in biomolecules, and can be potentially used in ion position prediction for given structures.

Assessment of the transmembrane domain structures in GPCR Dock 2013 models.

The community-wide blind prediction of G-protein coupled receptor (GPCR) structures and ligand docking has been conducted three times and the quality of the models was primarily assessed by the accuracy of ligand binding modes. The seven transmembrane (TM) helices of the receptors were taken as a whole; thus the model quality within the 7TM domains has not been evaluated. Here we evaluate the 7TM domain structures in the models submitted for the last round of prediction - GPCR Dock 2013. Applying the 7 × 7 RMSD matrix analysis described in our prior work, we show that the models vary widely in prediction accuracy of the 7TM structures, exhibiting diverse structural differences from the targets. For the prediction of the 5-hydroxytryptamine receptors, the top 7TM models are rather close to the targets, which however are not ranked top by ligand-docking. On the other hand, notable deviations of the TMs are found in in the previously identified top docking models that closely resemble other receptors. We further reveal reasons of success and failure in ligand docking for the models. This current assessment not only complements the previous assessment, but also provides important insights into the current status of GPCR modeling and ligand docking.

Predictive Factors of Skip Metastasis in Papillary Thyroid Cancer.

BACKGROUND Skip metastasis is defined as metastasis incident to the lateral compartment without involvement of the central compartment, and is generally unpredictable in papillary thyroid cancer (PTC). The present study aimed to investigate the frequency and predictor value of skip metastasis in PTC patients. MATERIAL AND METHODS A total of 355 patients diagnosed with thyroid cancer who had received a prior complete thyroidectomy with bilateral central neck and ipsilateral lateral neck lymph node dissection were enrolled in this study. The clinicopathological and ultrasound features were analyzed. A univariate and multivariate analysis were performed to identify the risk factors of skip metastasis. RESULTS The frequency of skip metastasis was 12.4% (44/355). The PTC patients with skip metastasis exhibited fewer lymph node metastasis, which was more commonly detected in tumor size ≤1 cm (OR 9.354; p=0.001; 95% confidence interval (CI) 1.865-26.735), tumors located in upper pole (OR 3.822; p<0.001; 95% CI 1.935-7.549), without a well-defined margin (OR 2.528; p=0.016; CI 1.191-5.367), and extrathyroidal extension (OR 2.406; p=0.013; CI 1.691-4.367). CONCLUSIONS Skip metastasis was common in PTC. The PTC patients with a tumor size ≤1.0 cm, located in the upper pole, without a well-defined margin and extrathyroidal extension should be carefully evaluated for skip metastasis.

7×7 RMSD matrix: A new method for quantitative comparison of the transmembrane domain structures in the G-protein coupled receptors.

The G-protein coupled receptors (GPCRs) share a conserved heptahelical fold in the transmembrane (TM) region, but the exact arrangements of the seven TM helices vary with receptors and their activation states. The differences or the changes have been observed in the experimentally solved structures, but have not been systematically and quantitatively investigated due to lack of suitable methods. In this work, we describe a novel method, called 7×7 RMSD matrix that is proposed specifically for comparing the characteristic 7TM bundle structures of GPCRs. Compared to the commonly used overall TM bundle RMSD as a single parameter, a 7×7 RMSD matrix contains 49 parameters, which reveal changes of the relative orientations of the seven TMs. We demonstrate the novelty and advantages of this method by tackling two problems that are challenging for the existing methods. With this method, we are able to identify and quantify the helix movements in the activated receptor structures and reveal structural conservation and divergence as well as the structural relationships of different GPCRs in terms of the relative orientations of the seven TMs.

Upregulation of CD44v6 contributes to acquired chemoresistance via the modulation of autophagy in colon cancer SW480 cells.

The CD44 isoform containing variant exon v6 (CD44v6) plays an important role in the progression, metastasis, and prognosis of colorectal cancer (CRC). Recently, it was found that CD44v6 is involved in acquired drug resistance. This study aimed to investigate the molecular mechanism of CD44v6 in the resistance of CRC cells to chemotherapy. A stable CD44v6 overexpression model in SW480 cells was established via lentiviral transduction. The chemosensitivity of cells to 5-fluorouracil (5-FU) and oxaliplatin (L-OHP) was determined by cell counting kit (CCK)-8, lactate dehydrogenase (LDH) release, and colony formation assays. Immunohistochemical staining of CD44v6 was performed in human CRC tissues. The key components in cell apoptosis, drug efflux and metabolism, mismatch repair, autophagy, epithelial-mesenchymal transition (EMT), and the PI3K-Akt and MAPK-Ras-Erk1/2 pathways were assessed using flow cytometry, quantitative real-time polymerase chain reaction (PCR), and western blot assays. The CD44v6 overexpression cells showed a higher viability, a lower LDH release rate, and an increased clonogenicity than the control cells under drug treatment. Moreover, overexpression of CD44v6 resulted in enhanced autophagy flux, EMT, and phosphorylation of Akt and Erk in the presence of drugs. Furthermore, high CD44v6 expression in the primary tumor was closely associated with an early recurrence in CRC patients who underwent curative surgery and adjuvant chemotherapy. In conclusion, overexpression of CD44v6 contributes to chemoresistance in SW480 cells under cytotoxic stress via the modulation of autophagy, EMT, and activation of the PI3K-Akt and MAPK-Ras-Erk pathways.

TamGen: drug design with target-aware molecule generation through a chemical language model.

Generative drug design facilitates the creation of compounds effective against pathogenic target proteins. This opens up the potential to discover novel compounds within the vast chemical space and fosters the development of innovative therapeutic strategies. However, the practicality of generated molecules is often limited, as many designs focus on a narrow set of drug-related properties, failing to improve the success rate of subsequent drug discovery process. To overcome these challenges, we develop TamGen, a method that employs a GPT-like chemical language model and enables target-aware molecule generation and compound refinement. We demonstrate that the compounds generated by TamGen have improved molecular quality and viability. Additionally, we have integrated TamGen into a drug discovery pipeline and identified 14 compounds showing compelling inhibitory activity against the Tuberculosis ClpP protease, with the most effective compound exhibiting a half maximal inhibitory concentration (IC50) of 1.9 µM. Our findings underscore the practical potential and real-world applicability of generative drug design approaches, paving the way for future advancements in the field.

A scoring function for the prediction of protein complex interfaces based on the neighborhood preferences of amino acids.

Proteins often assemble into functional complexes, the structures of which are more difficult to obtain than those of the individual protein molecules. Given the structures of the subunits, it is possible to predict plausible complex models via computational methods such as molecular docking. Assessing the quality of the predicted models is crucial to obtain correct complex structures. Here, an energy-scoring function was developed based on the interfacial residues of structures in the Protein Data Bank. The statistically derived energy function (Nepre) imitates the neighborhood preferences of amino acids, including the types and relative positions of neighboring residues. Based on the preference statistics, a program iNepre was implemented and its performance was evaluated with several benchmarking decoy data sets. The results show that iNepre scores are powerful in model ranking to select the best protein complex structures.

Determining pair distance distribution function from SAXS data using parametric functionals.

Small angle X-ray scattering (SAXS) experiments are widely applied in structural biology. The SAXS experiments yield one-dimensional profile that needs further analysis to reveal structural information. The pair distance distribution function (PDDF), P(r), can provide molecular structures more intuitively, and it can be used to guide ab initio model reconstructions, making it a critical step to derive P(r) from experimental SAXS profiles. To calculate the P(r) curves, a new method based on a specially designed parametric functional form is developed, and implemented in pregxs. This method is tested against both synthetic and experimental data, the estimated P(r) functions are in good agreement with correct or known P(r). The method can also predict the molecular size. In summary, the pregxs method is robust and accurate in P(r) determination from SAXS profiles. The pregxs source code and an online server are available at http://www.sastbx.als.lbl.gov.