Pharmacological activity and druggability are two pivotal factors in drug innovation, which are respectively determined by the microscopic structure and macroscopic property of a molecule. Since structural optimization consists in a molecular operation in the space with multi-dimensions, and there exists a body of uncertainties for transduction from in vitro activity into in vivo pharmacological response. It is necessary for early stage in lead optimization to evaluate compound quality or efficiency using a kind of metrics containing multi-parameters. On the basis of the describing parameters of activity and druggability, this overview deals with the roles of thermodynamic signatures and binding kinetics of drug-receptor interactions in optimizing quality of compounds, signifying the significance in optimization of microscopic structures for drug discovery.
Drug Design ; Drug Discovery ; methods ; Ligands ; Molecular Structure ; Pharmaceutical Preparations ; chemical synthesis ; chemistry ; Pharmacokinetics ; Pharmacology ; Protein Binding ; Receptors, Drug ; chemistry ; Structure-Activity Relationship ; Thermodynamics

Taking patient needs as the core and realizing clinical value as the guidance are the purpose and path of drug discovery. Whether the first-in-class drug or follow-on drugs are all to meet the demands of patients for drugs that are not treatable or more safe and effective. In order to realize clinical value, innovative drugs driven by basic biological research include three elements: understanding the molecular mechanism of pathogenesis; Grasping the microscopic features of the disease; clarifying the mechanism of action of drugs. The interrelation among the three is the translational medicine, and the medicinal chemistry plays an important role in the translations. That is, based on the results of basic research in biology/medicine, knowledge of the molecular mechanism of disease depends upon the establishment of various in vitro/in vivo models to find the key node and molecular regulation for the treatment of disease. Combined with the knowledge of gene deletion and variation, proteomics, epigenetics and other technologies, the molecular mechanism of disease provides multi-molecular information on the level of gene, proteins, enzymes, receptors, ion channels and signal transduction for molecular drug design. Insight into the microscopic characteristics of diseases would deepen the understanding of the molecular mechanism of the pathogenesis, as well as provide a feasible scientific path for the creation of new drugs. When the molecular mechanism of disease and the action mechanism of drugs are clarified, we have a deeper and wider understanding of the application of existing drugs (or active compounds), and may offer new ideas for drug design and application. In this translational process the medicinal chemistry plays a key role which requires medicinal chemists to break through the habitual thinking and working mode, backtracking (upstream) to basic research and its achievements and applying to the direction of creating new drugs in time, as well as paying attention to the clinical requirements (downstream) and implementing the specific content of the transformation process for the R&D of innovative drugs.

Artificial intelligence-aided drug discovery (AIDD) is a new version of computer-aided drug discovery (CADD). AIDD is featured in significantly promoting the performance of conventional CADD. AI markedly enhances the learning ability of CADD. In the 1960s, CADD was established from conventional QSAR approaches, which mainly used regression approaches to derive substructure-activity relationship for compounds with a common scaffold, and guide drug molecular design, figure out the binding features of drugs, and identify potential drug targets. Since the 1990s, structural biology has provided three-dimensional structures of drug targets, enabling drug discovery based on target structure (SBDD), fragment-based drug discovery (FBDD), and structure-based virtual screening (SBVS) with CADD approaches. In the past 30 years, many first in class (FIC) and best in class (BIC) drugs were discovered with CADD. Now, AIDD will further revolutionize CADD by reducing human interventions and mining big chemical and biological data. It is expected that AIDD will significantly enhance the abilities of CADD, virtual screening and drug target identification. This article tries to provide perspectives of CADD and AIDD in medicinal chemistry with case studies.

The binding of small molecule drugs to targets is mostly through non-covalent bonds, and hydrogen bond, electrostatic, hydrophobic and van der Waals interactions function to maintain the binding force. The more these binding factors lead to strong bindings and high activities. However, it is often accompanied by the increase of molecular size, resulting in pharmacokinetic problems such as membrane penetration and absorption, as well as metabolism, which ultimately affects the drug success. Fragment-based drug discovery (FBDD) is to screen high-quality fragment library to find hits. Combine with structural biology, FBDD generates lead compounds by means of fragment growth, linking and fusion, and finally drug candidates by the optimization operation. During the value chain FBDD is closely related to structure-based drug discovery (SBDD). In this paper, the principle of FBDD is briefly described by several launched drugs.

Although small molecule drugs (SMD) are still mainstream for the treatment of diseases, large molecule biologicss of many advantages, pose a challenge to the further discovery and use of SMD. The advantages of SMD are the convenience of oral administration and good patient compliance. However, the challenge with SMD is to integrate the PD, PK, selectivity and safety into a chemical structure. Because of their small size and surface area they often bind to various proteins, and off-target actions can cause adverse reactions. In this sense, selectivity is critical. Based upon target as the core to construct a chemical structure, it is necessary to consider the requirements of all the attributes, but achievement of the full-dimensional optimization is difficult. Modern drug discovery has been greatly enhanced by molecular biology and structural biology, and new strategies and technologies have emerged, which have created many successful medicines. For example, under the guidance of structural biology, covalent binding drugs connect moderate "electrophilic warheads" to the appropriate positions of molecules, and upon binding to their targets the electrophiles are irreversibly linked to the target by covalent bonds. Molecular biology can be directly applied to the development of antibody-coupled drugs (ADC). The antibody (A) acts as a carrier and a guide (for PK), and carries toxic molecules (D) into cancer cells, thus playing a killing role (for PD). The separate pharmacodynamic and pharmacokinetic entities are coupled (C) by linkers. PROTACs are also bifunctional molecules, which recruit a target protein and ubiquitin ligase E3 to form a ternary complex, which then acts as a catalyst to ubiquitinate the target protein and lead to degradation by the proteasome. In addition, in recent years, the combination of two fixed-dose drugs has improved selectivity, safety, and long-term benefit with many severe diseases, and can be regarded as an innovative strategy of physical combination. This review discusses some successful examples to briefly present the principles from the perspective of medicinal chemistry and therapeutic application.

Alternative splicing of pre-messenger RNA (pre-mRNA) is a crucial mechanism for the diversity of the human transcriptome and proteome. Alternative splicing is a complex gene regulation process. Whole-transcriptome analysis shows that 95% of human exonic genes are alternatively spliced, involving various cis-acting elements and trans-acting factors. Any changes in any component or step may cause erroneous splicing events and lead to the occurrence of various related diseases. In addition to gene replacement therapy that directly changes the splicing results, RNA splicing modification is expected to become a new therapeutic strategy to alleviate or treat diseases by targeting and correcting abnormal pre-mRNA splicing. Splicing modification tools currently developed including RNA trans-splicing, antisense oligonucleotides, small interfering RNA, and small molecule drugs can correct abnormal splicing through different ways. This article reviews the resent progress of epigenetic regulation of pre-mRNA alternative splicing in recent years, and discusses the occurrence and regulation of alternative splicing, the types of diseases caused by related splicing defects, and the current-used tools for targeting and altering splicing. The importance of splicing modification strategies in the future treatment of human diseases is envisioned.

Objective:To investigate the effects of sleep quality on cognitive function in elderly patients undergoing hemodialysis.Methods:In this cross-sectional study, the cognitive function in hemodialysis patients was evaluated by Montreal Cognitive Assessment(MoCA)and the sleep quality was accessed by Pittsburgh sleep quality index(PSQI). The related indexes of cognitive function were compared and the relationship between cognitive function and sleep quality was analyzed by using multiple binary Logistic regression method.Results:A total of 121 elderly hemodialysis patients aged 67.4±7.2 years with cognitive impairment of 76 cases(62.8%)were included in the study.Numbers(%)of cases with very good, good, general and poor sleep quality were 33(27.3%), 39(32.2%), 14(11.6%)and 35(28.9%), respectively.The proportion of patients with pretty good sleep quality was lower in cognitive impairment group than in normal cognitive group(13/76 or 17.1% vs.20/45 or 44.4%, P<0.001). The proportion of patients with poor sleep quality was higher in cognitive impairment group than in normal cognitive group(29/76 or 38.2% vs.6/45 or 13.3%, P<0.05). Multiple binary Logistic regression analysis showed that age( OR: 1.128, 95% CI: 1.083-1.175, P<0.001), a education level( OR: 0.353, 95% CI: 0.151-0.556, P<0.05), hypertension( OR: 2.508, 95% CI: 1.189-5.291, P<0.05), diabetes( OR: 1.913, 95% CI: 1.045-3.502, P<0.05), stroke( OR: 4.044, 95% CI: 1.439-11.365, P<0.05), dialysis age( OR: 1.016, 95% CI: 1.010-1.023, P<0.001), KT/V( OR: 0.025, 95% CI: 0.005-0.122, P<0.001)and parathormon(iPTH)( OR: 1.002, 95% CI: 1.000-1.003, P<0.05)were associated with cognitive impairment.After adjusting for above factors, sleep quality was also correlated with cognitive impairment( OR: 1.180, 95% CI: 1.108-1.258, P<0.001), showing that the risk of cognitive impairment increased by 1.18 times with every one point increase in PSQI scores. Conclusions:Cognitive impairment is associated with age, education level, hypertension, diabetes, stroke, dialysis age, KT/V and iPTH in elderly hemodialysis patient, and sleep quality is also an independent risk factor for cognitive impairment.

OBJECTIVE: Although the therapeutic method of stroke is progressed very quickly in recent years, the incidence of its post-depression is up to 40%. Poststroke depression many affect neural function recovery, for which, to understand it is advantageous of improving living quality of stroke patients.DATA SOURCE: The literatures relevant to poststroke depression were looked up from China medical nuclear journals and studies at home and abroad in recent 5 years on www.google.com, Medline. The Retrieval words: stroke, depression, incidence, relevant factors.STUDY SELECTION: Totally 42 relevant papers were selected on experimental and clinical studies on poststroke depression. The original literatures of non-randomized study were excluded and those of nonblind study were not excluded.DATA EXTRACTION: Of 42 papers, 10 papers were deleted because of repetition of various degrees and 32 papers were sorted out in category and 10 of those were selected as reference.DATA SYNTHESIS: The incidence of poststroke depression is about 40%, resulting from the co-factors of society, psychology and biology.It is viewed generally that the high risk phase of depression is in a couple of year after stroke and the duration of poststroke depression is various. The severity of neural functional deficits in recovery phase is affected by poststroke depression. Moderate and severe depression may delay the recovery of neural function and poststroke depression can also result in poor recovery of daily living capacity of patients, affect patients' cognition and increase the incidence of dementia. Concerning to clinical observation, a remarkable progression has been achieved on treatment of poststroke depression.CONCLUSION: The incidence of poststroke depression is very high,associated with multiple factors. Poststroke depression influences harmfully on neural function, cognition and daily living capacity. Active intervention and treatment provide a certain action on reducing the incidence of poststroke depression.

A number of reports have appeared implicating neurotoxicity of local anesthetics as a possible cause of neurologic complications after spinal anesthesia. Transient neurologic syndrome is one of neurologic complications. This article reviews the etiology, occurred mechanism, clinical symptoms, risk factors, prevention and treatment of transient neurologic syndrome.

Body Fluids ; cytology ; Cytodiagnosis ; methods ; Humans ; Immunohistochemistry ; methods ; Lung Neoplasms ; pathology ; Pleural Effusion, Malignant ; pathology ; Quality Control ; Specimen Handling ; standards